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Acute kidney injury (AKI) is a significant complication in burn patients, impacting outcomes substantially. This study explores the heterogeneity of AKI in burn patients by analyzing creatinine time-series data to identify distinct AKI clusters and evaluating routine biomarkers' predictive values. A retrospective cohort analysis was performed on 2608 adult burn patients admitted to Hangang Sacred Heart Hospital's Burn Intensive Care Unit (BICU) from July 2010 to December 2022. Patients were divided into four clusters based on creatinine trajectories, ranging from high-risk, severe cases to lower-risk, short-term care cases. Cluster A, characterized by high-risk, severe cases, showed the highest mortality and severity, with significant predictors being PT and TB. Cluster B, representing intermediate recovery cases, highlighted PT and albumin as useful predictors. Cluster C, a low-risk, high-resilience group, demonstrated predictive values for cystatin C and eGFR cys. Cluster D, comprising lower-risk, short-term care patients, indicated the importance of PT and lactate. Key biomarkers, including albumin, prothrombin time (PT), cystatin C, eGFR cys, and total bilirubin (TB), were identified as significant predictors of AKI development, varying across clusters. Diagnostic accuracy was assessed using area under the curve (AUC) metrics, reclassification metrics (NRI and IDI), and decision curve analysis. Cystatin C and eGFR cys consistently provided significant predictive value over creatinine, with AUC values significantly higher (p < 0.05) in each cluster. This study highlights the need for a tailored, biomarker-driven approach to AKI management in burn patients, advocating for the integration of diverse biomarkers in clinical practice to facilitate personalized treatment strategies. Future research should validate these biomarkers prospectively to confirm their clinical utility.
Subject(s)
Acute Kidney Injury , Biomarkers , Burns , Humans , Biomarkers/blood , Burns/complications , Burns/blood , Acute Kidney Injury/diagnosis , Acute Kidney Injury/blood , Acute Kidney Injury/etiology , Male , Female , Middle Aged , Adult , Retrospective Studies , Creatinine/blood , Cystatin C/blood , Aged , Glomerular Filtration RateABSTRACT
Acute Respiratory Distress Syndrome (ARDS) is a critical form of Acute Lung Injury (ALI), challenging clinical diagnosis and severity assessment. This study evaluates the potential utility of various hematological markers in burn-mediated ARDS, including Neutrophil-to-Lymphocyte Ratio (NLR), Mean Platelet Volume (MPV), MPV-to-Lymphocyte Ratio (MPVLR), Platelet count, and Platelet Distribution Width (PDW). Employing a retrospective analysis of data collected over 12 years, this study focuses on the relationship between these hematological markers and ARDS diagnosis and severity in hospitalized patients. The study establishes NLR as a reliable systemic inflammation marker associated with ARDS severity. Elevated MPV and MPVLR also emerged as significant markers correlating with adverse outcomes. These findings suggest these economical, routinely measured markers can enhance traditional clinical criteria, offering a more objective approach to ARDS diagnosis and severity assessment. Hematological markers such as NLR, MPV, MPVLR, Platelet count, and PDW could be invaluable in clinical settings for diagnosing and assessing ARDS severity. They offer a cost-effective, accessible means to improve diagnostic accuracy and patient stratification in ARDS. However, further prospective studies are necessary to confirm these findings and investigate their integration with other diagnostic tools in diverse clinical settings.
Subject(s)
Biomarkers , Burns , Respiratory Distress Syndrome , Severity of Illness Index , Humans , Respiratory Distress Syndrome/blood , Respiratory Distress Syndrome/diagnosis , Retrospective Studies , Female , Male , Biomarkers/blood , Middle Aged , Adult , Burns/blood , Burns/complications , Neutrophils/metabolism , Mean Platelet Volume , Platelet Count , Lymphocytes/metabolism , AgedABSTRACT
BACKGROUND: Although routine changing of central venous catheters (CVCs) is commonly performed in patients with severe burns, information on pathogen colonization of the CVC tip and associated bloodstream infections (BSIs) is limited in those patients. METHODS: The medical records of 214 patients with severe burns who underwent routine CVC changing at 7-day intervals and their results of 686 pairs of CVC tips and concurrent blood cultures were retrospectively reviewed to evaluate the CVC colonization rate and associated BSI pathogens. RESULTS: Of the 686 CVCs, 137 (20.0%) were colonized by pathogens, and 81 (59.1%) of them had BSIs caused by the same pathogen. Nonflame burn (P = .002), total body surface area burn ≥30% (P = .004), femoral catheterization (P = .001), CVC changing during pre-existing BSI (P < .001), and renal replacement therapy (P = .017) were associated with catheter-related BSI in the multivariate analysis. Most BSIs were caused by Gram-negative bacteria (most commonly Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa). CONCLUSIONS: The CVC colonization rate in patients with severe burns and routine CVC changing was not high. Lengthening the CVC duration might be attempted in patients at a lower risk of catheter-related BSI although further prospective studies are necessary.
Subject(s)
Burns , Catheter-Related Infections , Central Venous Catheters , Humans , Burns/complications , Burns/microbiology , Male , Female , Middle Aged , Retrospective Studies , Central Venous Catheters/adverse effects , Central Venous Catheters/microbiology , Adult , Catheter-Related Infections/microbiology , Catheter-Related Infections/epidemiology , Aged , Young Adult , Bacteremia/microbiology , Bacteremia/epidemiology , Bacteremia/etiology , Adolescent , Aged, 80 and over , Bacteria/isolation & purification , Bacteria/classification , Catheterization, Central Venous/adverse effectsABSTRACT
An analytical method using GC-MS/MS combined with quick, easy, cheap, effective, rugged, and safe extraction was developed to determine 57 pesticides in fishery products. The limits of detection and quantification (LOD and LOQ, respectively) of the analytical method ranged between 0.91 and 2.12 ng/g wet mass and 3 and 7 ng/g wet mass, respectively. Moreover, the linearity of the calibration curves was acceptable (R2 > 0.99). The relative pesticide recoveries ranged between 53.87 and 127.2%, and reproducibility ranged between 0.25 and 10.87%. The pesticide residues in brown seaweed, eel, flatfish, shrimp, and abalone samples were analyzed using the developed analytical method, and the results indicate that most samples were not contaminated by the 57 target pesticides, except low levels (< 10 ng/g) of 1,1-dichloro-2,2-bis(4-chlorophenyl)ethene, alachlor, ametryn, isoprothiolane, and prometryn in several samples.
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Sepsis and septic shock are prevalent and life-threatening complications in burn patients. Despite their severity, existing diagnostic methods are limited. This study aims to evaluate the efficacy of Complete Blood Count (CBC) and CBC ratio markers in diagnosing sepsis and septic shock, and in predicting mortality among burn patients. A cohort of 2757 burn patients was examined to ascertain the correlation between various CBC parameters, their ratios, and the incidence of sepsis and related mortality. Key markers analyzed included Red Cell Distribution Width (RDW), Mean Platelet Volume (MPV), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Mean Platelet Volume-to-Platelet Ratio (MPVPR). Our findings indicate that 65.5% of the patients developed sepsis, and 24.3% succumbed to their conditions. The CBC parameters RDW, MPV, NLR, MPVPR, and MPV-to-Lymphocyte Ratio (MPVLR) were significantly associated with sepsis and mortality. These markers showed considerable temporal variation and yielded an Area Under the Curve (AUC) of over 0.65 in an unadjusted Generalized Estimating Equations (GEE) model. This study underscores the potential of RDW, MPV, NLR, MPVPR, and MPVLR as vital prognostic tools for diagnosing sepsis, septic shock, and predicting mortality in burn patients. Although based on a single-center dataset, our results contribute to the enhancement of sepsis management by facilitating earlier, more precise diagnosis and treatment strategies. Further multi-center research is necessary to confirm these findings and broaden their applicability, establishing a solid base for future explorations in this crucial field.
Subject(s)
Burns , Sepsis , Shock, Septic , Humans , Shock, Septic/diagnosis , Retrospective Studies , Big Data , Sepsis/diagnosis , Blood Cell Count , Burns/complicationsABSTRACT
This study aims to evaluate the utility of complete blood count (CBC) markers, in conjunction with the acute kidney injury network (AKIN) criteria, for the early detection, severity assessment, and prediction of mortality outcomes of acute kidney injury (AKI) in burn patients. The research seeks to fill existing gaps in knowledge and validate the cost-effectiveness of using CBC as a routine diagnostic tool for better management of AKI. The study was conducted at Hangang Sacred Heart Hospital. We performed a large-scale retrospective analysis of 2758 adult patients admitted to the burn intensive care unit over a 12-year period. Among these patients, AKI occurred in 1554 patients (56.3%). Based on the AKIN stage classification, 794 patients (28.8%) were categorized as AKIN 1, 494 patients (17.9%) as AKIN 2, and 266 patients (9.6%) as AKIN 3. We defined several ratio markers, including the Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and various mean platelet volume (MPV) ratios. Our statistical analyses, conducted using the R programming language, revealed significant correlations between these markers and AKI severity. The AUC values for neutrophil count and WBC count were 0.790 and 0.793, respectively, followed by immature granulocyte count with an AUC of 0.727. For red blood cell (RBC)-related parameters, the AUC values for hematocrit (Hct), hemoglobin (Hb), and RBC count were 0.725, 0.713, and 0.713, respectively. Among the platelet-related parameters, only platelet distribution width (PDW) had an AUC of 0.677. Among the ratio markers, the NLR had the highest AUC at 0.772, followed by MPVNR and SII with AUC values of 0.700 and 0.680, respectively. The findings underscore the potential of CBC as an economical, routine test for AKI, thereby paving the way for enhanced patient outcomes. Our study suggests the utility of routine CBC tests, specifically WBC count and PLR, for predicting AKI and platelet, MPV, and NLR for mortality assessment in burn patients. These findings underscore the potential of easily accessible CBC tests in enhancing AKI management. However, further multicenter studies are needed for validation.
Subject(s)
Acute Kidney Injury , Adult , Humans , Retrospective Studies , Blood Cell Count , Leukocyte Count , Hematocrit , Acute Kidney Injury/diagnosisABSTRACT
Background: Sepsis is a potentially life-threatening condition that occurs when the body's response to infection leads to widespread inflammation and tissue damage. Negative cultures can make it difficult for clinicians to make a diagnosis and may raise questions about the validity of the definition of sepsis. In addition, the clinical distinctions between burn patients with blood culture-positive and -negative sepsis are also poorly understood. Therefore, this study aimed to examine the clinical differences between blood culture-positive and -negative sepsis in burn patients in order to improve the understanding of the pathophysiology and epidemiology of sepsis in this population. Methods: This study had a retrospective design, and the participants were adults aged ≥18 years. Patients diagnosed with sepsis were divided into two groups based on their blood culture results within 1 week of sepsis diagnosis. Results: We enrolled 1643 patients admitted to our institution's burn intensive care unit between January 2010 and December 2021. pH, platelet count, bicarbonate and haematocrit were significant in both the positive and negative groups. However, lymphocyte, red cell distribution width and blood urea nitrogen were significant only in the positive group, whereas lactate dehydrogenase was significant only in the negative group. Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumonia are common gram-negative bacterial species, and Staphylococcus aureus and Staphylococcus epidermidis are common gram-positive bacterial species seen in burn patients with positive blood cultures. Carbapenem resistance was found to be associated with an unfavourable prognosis in gram-negative bacteria, with the exception of P. aeruginosa. Conclusions: pH, platelet count, bicarbonate and haematocrit were routine biomarkers that demonstrated statistical significance in both groups. Lactate dehydrogenase was significant in the blood-negative group, while red cell distribution width, blood urea nitrogen and lymphocyte count were significant in the positive group. Furthermore, the most common causes of sepsis are gram-negative bacteria, including A. baumannii, K. pneumoniae and P. aeruginosa. Additionally, resistance to carbapenems is associated with unfavourable outcomes.
ABSTRACT
BACKGROUND: Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with increased morbidity and mortality. Patients with burns are particularly vulnerable to developing sepsis and AKI due to the extensive tissue damage and immune suppression resulting from burn injury. In this study, unsupervised clustering algorithms were used to track longitudinal biomarkers in patients with burns and assess their impact on mortality. METHODS: This retrospective study included adult patients with burns aged ≥ 18 years, who were admitted to the burn intensive care unit of Hallym University and Hangang Sacred Heart Hospital between July 2010 and December 2021. The patients were divided into two subgroups: those with sepsis (538 patients) and those without sepsis (826 patients). The longitudinal biomarkers were grouped into three clusters using the k-means clustering algorithm. Each cluster was assigned a letter from A to C according to its mortality rate. RESULTS: The odds ratio (OR) of pH was 9.992 in the positive group and 31.745 in the negative group in cluster C. The OR for lactate dehydrogenase (LD) was 3.704 in the positive group and 6.631 in the negative group in cluster C. The OR for creatinine was 2.784 in the positive group and 8.796 in the negative group in cluster C. The OR for blood urea nitrogen (BUN) in the negative group was 0.348, indicating a negative predictor of mortality. Regarding the application of Continuous Renal Replacement Therapy (CRRT) and ventilation, ventilation was significant in both groups. In contrast, CRRT application was not significant in the sepsis-positive group. Furthermore, it was not selected as a variable in the negative group. CONCLUSIONS: The pH, LD, and creatinine were significant in both groups, while lactate and platelets were significant in the sepsis-positive group. In addition, albumin, glucose, and BUN were significant in the sepsis-negative group. Continuous renal replacement therapy was not significant in either group. However, the use of a ventilator was associated with poor prognosis.
Subject(s)
Acute Kidney Injury , Sepsis , Adult , Humans , Creatinine , Retrospective Studies , Acute Kidney Injury/etiology , Sepsis/complications , Biomarkers , Cluster Analysis , L-Lactate DehydrogenaseABSTRACT
Burn injuries often result in a high level of clinical heterogeneity and poor prognosis in patients with severe burns. Clustering algorithms, which are unsupervised methods that can identify groups with similar trajectories in patients with heterogeneous diseases, can provide insights into the mechanisms of the disease pathogenesis. This study aimed to analyze routinely collected biomarkers to understand their mortality prediction power, identify the clinical meanings or subtypes, and inform treatment decisions to improve the outcomes of patients with burns. This retrospective cohort study included patients aged ≥ 18 years who were admitted between January 2010 and December 2021. The patients were divided into four subgroups based on the time period of their admission: week 1, 2, 3, and 4. The study revealed that 22 biomarkers were evaluated, and the red blood cell distribution width, bicarbonate level, pH, platelets, and lymphocytes were significantly associated with the mortality risk. Latent class analysis further demonstrated that the pH, platelets, lymphocytes, lactate, and albumin demonstrated the lowest levels in the cluster with the highest risk of mortality, with the lowest levels of pH and lactate being particularly noteworthy in week 1 of the study. During the week 2, the pH and lymphocyte levels were demonstrated to be significant predictors of the mortality risk, whereas the lymphocyte and platelet counts were meaningful predictors in week 3. During week 4, pH, platelet count, and albumin level were important predictors of mortality risk. Analysis of routinely collected biomarkers using clustering algorithms and latent class analysis can provide valuable insights into the heterogeneity of burn injuries and improve the ability to predict disease progression and mortality. Our findings suggest that lactate levels are a better indicator of cellular hypoxia in the early stages of burn shock, whereas platelet and lymphocyte levels are more indicative of infections such as sepsis. Albumin levels are considered a better indicator of reduced nutritional loss with decrease in unhealed burn wounds; however, the pH levels reflect the overall condition of the patient throughout the study period. These findings can be used to inform treatment decisions and improve the outcomes of burn patients.
Subject(s)
Burns , Lactic Acid , Humans , Latent Class Analysis , Retrospective Studies , Cluster Analysis , AlbuminsABSTRACT
Significance: Early assessment of local tissue oxygen saturation is essential for clinicians to determine the burn wound severity. Background: We assessed the burn extent and depth in the skin of the extremities using a custom-built 36-channel functional near-infrared spectroscopy system in patients with burns. Methods: A total of nine patients with burns were analyzed in this study. All second-degree burns were categorized as superficial, intermediate, and deep burns; non-burned skin on the burned side; and healthy skin on the contralateral non-burned side. Hemodynamic tissue signals from functional near-infrared spectroscopy attached to the burn site were measured during fNIRS using a blood pressure cuff. A nerve conduction study was conducted to check for nerve damage. Results: All second-degree burns were categorized into superficial, intermediate, and deep burns; non-burned skin on the burned side and healthy skin on the contralateral non-burned side showed a significant difference distinguishable using functional near-infrared spectroscopy. Hemodynamic measurements using functional near-infrared spectroscopy were more consistent with the diagnosis of burns 1 week later than that of the degree of burns diagnosed visually at the time of admission. Conclusion: Functional near-infrared spectroscopy may help with the early judgment of burn extent and depth by reflecting differences in the oxygen saturation levels in the skin.
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Purpose: Burn injury has high clinical heterogeneity and worse prognosis in severely burned patients. Clustering algorithms using unsupervised methods to identify groups with similar trajectories in heterogeneous disease patients can provide insight into mechanisms of disease pathogenesis. This study analyzed routinely collected biomarkers to evaluate mortality prediction, find clinical meanings for these or their subtypes, and evaluate patterns. Methods: This retrospective cohort study included patients aged >18 years, between July 2012 and June 2021. All eligible patients received fluid resuscitation and survived for at least 7 days. Characteristics of clinical interest to the physician at 4 clinically important time points were evaluated. Results: Eligible patients were divided into 4 subgroups according to these time points: from 1st week to 4th week. Total of 1,249 patients admitted within 2 days after burns and receiving fluid resuscitation were included. Mean Harrell's C-index of pH was the highest (0.816), followed by platelets (0.807), creatinine (0.796), red cell distribution width (RDW, 0.778), and lactate (0.759). Longitudinal profiles among biomarkers were different. Conclusion: The main predictors were pH, platelets, creatinine, RDW, and lactate. Creatinine and RDW showed consistent patterns. The other markers varied according to patient condition. Thus, these markers could provide clues into underlying mechanisms and predict mortality.
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PURPOSE: Sepsis-3 is a life-threatening organ dysfunction caused by dysregulated host responses to infection; and defined using the Sepsis-3 criteria, introduced in 2016, however, the criteria need to be validated in specific clinical fields. We investigated mortality prediction and compared the diagnostic performance of quick Sequential Organ Failure Assessment (qSOFA), systemic inflammatory response syndrome (SIRS), and burn-specific SIRS (bSIRS) in burn patients. METHODS: This single-center retrospective cohort study examined burn patients in Seoul, Korea during January 2010-December 2020. Overall, 1,391 patients with suspected infection were divided into four sepsis groups using SOFA, qSOFA, SIRS, and burn-specific SIRS. RESULTS: Hazard ratios (HRs) of all unadjusted models were statistically significant; however, the HR (0.726, p = 0.0080.001) in the SIRS ≥2 group is below 1. In the adjusted model, HRs of the SOFA ≥2 (2.426, <0.001), qSOFA ≥2 (7.198, p<0.001), and SIRS ≥2 (0.575, p<0.001) groups were significant. The diagnostic performance of dichotomized qSOFA, SIRS, and bSIRS for sepsis was defined by the Sepsis-3 criteria. The mean onset day was 4.13±2.97 according to Sepsis-3. The sensitivity of SIRS (0.989, 95% confidence interval [CI]: 0.982-0.994) was higher than that of qSOFA (0.841, 95% CI: 0.819-0.861) and bSIRS (0.803, 95% CI: 0.779-0.825). Specificities of qSOFA (0.929, 95% CI: 0.876-0.964) and bSIRS (0.922, 95% CI: 0.868-0.959) were higher than those of SIRS (0.461, 95% CI: 0.381-0.543). CONCLUSION: Sepsis-3 is a good alternative diagnostic tool because it reflects sepsis severity without delaying diagnosis. SIRS showed higher sensitivity than qSOFA and bSIRS and may therefore more adequately diagnose sepsis.
Subject(s)
Burns , Sepsis , Humans , Systemic Inflammatory Response Syndrome/diagnosis , Retrospective Studies , Organ Dysfunction Scores , Hospital Mortality , Sepsis/complications , Sepsis/diagnosis , Survival Analysis , Burns/complications , Prognosis , ROC Curve , Emergency Service, HospitalABSTRACT
This paper investigated the effects of femtosecond laser beam polarization on ablation efficiency and microstructure symmetricity for 64FeNi alloy (Invar) sheet processing to fabricate fine metal masks. It was found that the ablation efficiency for linear polarization was approximately 15% higher than that for circular polarization due to electric field enhancement induced by low-spatial-frequency laser-induced periodic surface structures (LIPSS). The hole size and sidewall taper angles for the microstructures generated by linear polarization were asymmetric, whereas those generated by circular polarization were symmetric due to non-oriented LIPSS. The asymmetric and symmetric three-dimensional microstructure profiles, measured by using a confocal laser scanning microscope, were verified by employing an analytical model that was derived using the total input fluence and the ablation rates for linear and circular polarizations, respectively.
ABSTRACT
Significance: Electrical burns can cause severe damage to the nervous system, resulting in autonomic dysfunction with reduced cerebral perfusion. However, few studies have investigated these consequences. Aim: To elucidate changes in prefrontal cerebral hemodynamics using functional near-infrared spectroscopy (fNIRS) during the head-up tilt table test (HUT) for patients with electrical burns. Approach: We recruited 17 patients with acute electrical burns within 1 week after their accidents and 10 healthy volunteers. The NIRS parameters acquired using an fNIRS device attached to the forehead were analyzed in five distinct HUT phases. Results: Based on their HUT response patterns, patients with electrical burns were classified into the group with abnormal HUT results (APG, n = 4) or normal HUT results (NPG, n = 13) and compared with the healthy control (HC, n = 10) participants. We found trends in hemodynamic changes during the HUT that distinguished HC, NPG, and APG. Reduced cerebral perfusion and decreased blood oxygenation during the HUT were found in both the NPG and APG groups. Patients with electrical burns had autonomic dysfunction compared to the HC participants. Conclusions: Using fNIRS, we observed that acute-stage electrical burn injuries could affect cerebral perfusion.
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Smart windows can selectively regulate excess solar radiation to reduce heating and cooling energy consumption in the built environment. However, the inevitable dissipation of ultraviolet and near-infrared into waste heat results in inefficient solar utilization. Herein, a dual-band selective solar harvesting (SSH) window is developed to realize full-spectrum utilization. A transparent photovoltaic, converting ultraviolet into electricity, and a transparent solar absorber, converting near-infrared into thermal energy, are integrated and coupled with a ventilation system to extract heat for indoor use. Compared with common transparent photovoltaics, the SSH window increases solar harvesting efficiency up to threefold while maintaining a considerable visible transmittance. Simulations suggest that the SSH window, besides generating electricity, delivers energy savings by over 30% higher than common smart windows. This is the first integration of transparent photovoltaic and transparent solar absorber into a window, which may open up a new avenue for the development of energy-efficient buildings.
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In this study, two bacterial species, Salipiger thiooxidans and Exiguobacterium aestuarii, were extracted and screened from the Saemangeum Reservoir. This study examined these species' suitability as a probiotic by confirming the effects of S. thiooxidans and E. aestuarii added to rearing water for L. vannamei. Three experimental groups were evaluated for 6 weeks: (1) a control group reared in natural (i.e., untreated) water (CON), (2) an experimental group in which S. thiooxidans was added to natural water (SMG-A), and (3) natural water inoculated with E. aestuarii (SMG-B). The SMG-B group inoculated with E. aestuarii showed significantly higher final body weight, weight gain, specific growth rates, and feed efficiency than the control group. The SMG-B group inoculated with E. aestuarii exhibited significantly higher levels of serum lysozyme, and ACP and ALP activity than the control and SMG-A groups. The SMG-A and SMG-B groups inoculated with probiotics showed significantly lower total ammonia nitrogen and nitrite than the control group. Our findings suggest that S. thiooxidans and E. aestuarii extracted from the Saemangeum Reservoir can improve the water quality of aquaculture water, and, in particular, E. aestuarii is a potential probiotic for L. vannamei.
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Adaptive control of solar and thermal radiation through windows is of pivotal importance for building energy saving. However, such synchronous passive regulations are challenging to be integrated into one thermochromic window. Here, we develop a solar and thermal regulatory (STR) window by integrating poly(N-isopropylacrylamide) (pNIPAm) and silver nanowires (AgNWs) into pNIPAm/AgNW composites. A hitherto unexplored mechanism, originating from the temperature-triggered water capture and release due to pNIPAm phase transition, is exploited to achieve simultaneous regulations of solar transmission and thermal emission. The STR window shows excellent solar modulation (58.4%) and thermal modulation (57.1%) and demonstrates effective regulation of indoor temperatures during both daytime and nighttime. Compared to other thermochromic technologies, the STR window reduces heat loss in cold environment while promotes heat dissipation in hot conditions, achieving efficient energy saving in all weathers. This dual solar and thermal regulation mechanism may provide unidentified insights into the advancement of smart window technology.
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Due to its high polyunsaturated fatty acid content, acellular fish skin has emerged as a dermal substitute for the promotion of wound healing as it decreases scar formation while providing pain relief. However, various systematic studies on acellular fish skin, such as its biophysical analysis, in vitro activities, and clinical application, have not been sufficiently investigated. In this study, we conducted a comparative study to evaluate the wound-healing ability of acellular fish skin graft (Kerecis®) with that of the widely used bovine collagen skin graft (ProHeal®). The skin grafts were evaluated not only in terms of their biophysical properties, but also their in vitro cellular activities, using fibroblasts, keratinocytes, and human endothelial cells. The clinical study evaluated wound healing in 52 patients with acute burns who underwent skin grafting on donor sites from January 2019 to December 2020. The study was conducted with two groups; while only Kerecis® was tested in one group, Kerecis® and ProHeal® were compared in the other. In both groups, the application time of the dressing material was one to two days after split-thickness skin grafting to the donor sites. The Kerecis®-treatment group experienced faster healing than the other treatment group. In particular, the average wound healing time using the Kerecis® treatment and the ProHeal® treatment was 10.7 ± 1.5 days and 13.1 ± 1.4 days, respectively. We believe that the faster healing of the Kerecis® treatment, compared to that of the ProHeal® treatment, maybe due to the synergistic effect of the unique biophysical structure and the bioactive components of acellular fish skin.
Subject(s)
Burns , Endothelial Cells , Animals , Burns/surgery , Cattle , Collagen/pharmacology , Humans , Skin Transplantation , Wound HealingABSTRACT
The aim of this study is to analyse the determinants of women's vaginal dryness using machine learning. Data came from Korea University Anam Hospital in Seoul, Republic of Korea, with 3298 women, aged 40-80 years, who attended their general health check from January 2010 to December 2012. Five machine learning methods were applied and compared for the prediction of vaginal dryness, measured by a Menopause Rating Scale. Random forest variable importance, a performance gap between a complete model and a model excluding a certain variable, was adopted for identifying major determinants of vaginal dryness. In terms of the mean squared error, the random forest (1.0597) was much better than linear regression (17.9043) and artificial neural networks with one, two and three hidden layers (1.7452, 1.7148 and 1.7736, respectively). Based on random forest variable importance, the top-10 determinants of vaginal dryness were menopause age, age, menopause, height, thyroid stimulating hormone, neutrophils, years since menopause, lymphocytes, alkaline phosphatase and blood urea nitrogen. In addition, its top-20 determinants were peak expiratory flow rate, low-density lipoprotein cholesterol, white blood cells, monocytes, cancer antigen 19-9, creatinine, eosinophils, total cholesterol, triglyceride and amylase. Machine learning presents a great decision support system for the prediction of vaginal dryness. For preventing vaginal dryness, preventive measures would be needed regarding early menopause, the thyroid function and systematic inflammation.Impact StatementWhat is already known on this subject? Only a few studies have investigated the risk factors of vaginal dryness in middle-aged women. More research is to be done for finding its various risk factors, identifying its major risk groups and drawing its effective clinical implications.What do the results of this study add? This study is the first machine-learning study to predict women's vaginal dryness and analyse their determinants. The random forest could discuss which factors are more important for the prediction of vaginal dryness. Based on random forest variable importance, menopause age was the most important determinant of vaginal dryness and their association was discovered to be negative in this study. Vaginal dryness was closely associated with the height, rather than the body weight or body mass index. The importance rankings of blood conditions related to systematic inflammation were within the top-20 in this study: neutrophils, lymphocytes, white blood cells, monocytes and eosinophils.What are the implications of these findings for clinical practice and/or further research? Machine learning presents a great decision support system for the prediction of vaginal dryness. For preventing vaginal dryness, preventive measures would be needed regarding early menopause and systematic inflammation.
Subject(s)
Artificial Intelligence , Vaginal Diseases , Cholesterol , Female , Hospitals, General , Humans , Inflammation , Menopause , Middle AgedABSTRACT
BACKGROUND: To analyze the factors associated with women's vasomotor symptoms (VMS) using machine learning. METHODS: Data on 3,298 women, aged 40-80 years, who attended their general health check-up from January 2010 to December 2012 were obtained from Korea University Anam Hospital in Seoul, Korea. Five machine learning methods were applied and compared for the prediction of VMS, measured by the Menopause Rating Scale. Variable importance, the effect of a variable on model performance, was used for identifying the major factors associated with VMS. RESULTS: In terms of the mean squared error, the random forest (0.9326) was much better than linear regression (12.4856) and artificial neural networks with one, two, and three hidden layers (1.5576, 1.5184, and 1.5833, respectively). Based on the variable importance from the random forest, the most important factors associated with VMS were age, menopause age, thyroid-stimulating hormone, and monocyte, triglyceride, gamma glutamyl transferase, blood urea nitrogen, cancer antigen 19-9, C-reactive protein, and low-density lipoprotein cholesterol levels. Indeed, the following variables were ranked within the top 20 in terms of variable importance: cancer antigen 125, total cholesterol, insulin, free thyroxine, forced vital capacity, alanine aminotransferase, forced expired volume in 1 second, height, homeostatic model assessment for insulin resistance, and carcinoembryonic antigen. CONCLUSION: Machine learning provides an invaluable decision support system for the prediction of VMS. For managing VMS, comprehensive consideration is needed regarding thyroid function, lipid profile, liver function, inflammation markers, insulin resistance, monocyte count, cancer antigens, and lung function.