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BACKGROUND: The incidence of necrotizing enterocolitis (NEC) is significantly associated with gestational age (GA). This study aimed to investigate risk factors for surgically treated NEC (sNEC) in extremely preterm infants (EPIs) using nationwide cohort registry. METHODS: Data were collected from 16,338 very-low-birth-weight infants registered in the Korean neonatal network. Clinical data of 5310 EPIs were retrospectively analyzed. sNEC was defined as infants with diagnosis of NEC requiring surgical treatment, who underwent surgical intervention for NEC or died before surgery. Infants were categorized into three groups based on their NEC status: infants without NEC (control), medically treated NEC (mNEC), and sNEC. These groups were matched based on GA to investigate risk factors for NEC. RESULTS: In EPIs, small for gestational age (SGA; odds ratio 1.68, 95% confidence interval [CI], 1.17-2.36, p = 0.004), hypotension (1.49, 1.18-1.89, p = 0.001), and IVH (1.63, 1.30-2.05, p < 0.001) were identified as risk factors for sNEC. Complete administration of antenatal steroid reduced the risk of sNEC (0.80, 0.64-0.99, p = 0.044). CONCLUSION: Our study demonstrated that EPIs who are SGA, and experience hypotension and IVH may be at an increased risk of developing NEC requiring surgery. These groups require close attention and monitoring for any signs of surgical indications of NEC. IMPACT: This nationwide cohort study aimed to identify characteristics of infants with necrotizing enterocolitis (NEC) among extremely preterm infants (EPIs) and analyze the risk factors associated with NEC requiring surgical intervention. Small for gestational age (SGA), hypotension, and intraventricular hemorrhage (IVH) were identified as significant risk factors for surgically treated NEC (sNEC) in EPIs. The administration of antenatal steroids decreases the risk of sNEC. Close attention and monitoring for EPIs with early identifiable risk factors such as SGA, hypotension, and IVH should be considered to prevent and detect sNEC early, ultimately leading to improved long-term outcomes.
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Purpose: After the declaration by the World Health Organization signaling the conclusion of the COVID-19 pandemic, most countries lifted mandatory mask-wearing regulations. This study aimed to investigate factors such as risk perception and political ideology associated with continued adherence to mask-wearing among specific populations, particularly when it is no longer deemed necessary. Methods: We conducted a cross-sectional study including a sample of 1001 respondents stratified by sex, age (≥ 18 years), and region from January 31 to February 2, 2023, after the mandatory mask regulation was lifted in South Korea. Multivariate logistic regression models were applied to estimate the relationships between risk perceptions, political ideology, and mask-wearing maintenance, adjusting for factors such as sex, age, occupation, and trust in the government. Results: Our results indicated significant associations between age, self-reported household economic status, political ideology, affective risk perception, and perceived effectiveness of the government's COVID-related measures with indoor mask-wearing. Specifically, liberals were more likely to keep mask-wearing indoors than conservatives (adjusted odds ratio [aOR]: 2.19; 95% confidence interval [CI]: 1.33-3.59); and those who perceived a greater affective risk of COVID-19 (aOR: 2.47; 95% CI: 1.96-3.10), along with those who perceived the government's countermeasures as inadequate, were more inclined to maintain the habit of wearing masks indoors (aOR: 1.90; 95% CI: 1.19-3.03). Conclusion: Our study highlighted the multifaceted factors influencing mask-wearing behavior in the post-COVID-19 era. Even after adjusting for various confounding factors, such as age, sex, and trust in the government, an association remained between affective risk perception, political ideology, and mask-wearing behavior. However, further research for psychological mechanisms is needed to foster a culture of preventive behaviors proportional to the risk of infection.
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Objectives: Salivary cortisol reflects the biologically active form of serum cortisol, offering a noninvasive evaluation method for the diurnal rhythm of the hypothalamic-pituitary-adrenal (HPA) axis. While liquid chromatography-tandem mass spectrometry (LC-MS/MS) is known for its specificity, immunoassays (IA) are commonly used because of their simplicity. This study aimed to assess the performance of salivary cortisol measurement using both IA and LC-MS/MS in comparison to serum-free cortisol measurement. Methods: Assay results for 188 saliva and 94 serum samples from 47 participants were analyzed. Salivary samples collected at different time points were analyzed using IA and LC-MS/MS. Serum samples were analyzed for cortisol, cortisol-binding globulin, and free cortisol. The statistical analyses included correlations and method comparisons. Results: The diurnal salivary cortisol profiles exhibited a comparable circadian rhythm pattern; however, the concentrations measured using IA were consistently higher than those measured using LC-MS/MS. The correlation analysis revealed robust associations among salivary cortisol (IA), salivary cortisol (LC-MS/MS), and serum-free cortisol levels (LC-MS/MS). However, the method comparison revealed a systematic bias between IA and LC-MS/MS in salivary cortisol measurement. Conclusions: This study contributes to the ongoing debate on assay techniques by affirming the suitability of IA and LC-MS/MS for salivary cortisol measurement to assess dynamic changes in HPA axis activity. The identified systematic bias emphasizes the importance of selecting methods based on specific research or clinical requirements.
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The textile industry contributes substantially to water pollution. To investigate bioremediation of dye-containing wastewater, the decolorization and biotransformation of three textile azo dyes, Red HE8B, Reactive Green 27, and Acid Blue 29, were considered using an integrated remediation approach involving the microalga Chlamydomonas mexicana and activated sludge (ACS). At a 5 mg L-1 dye concentration, using C. mexicana and ACS alone, decolorization percentages of 39%-64% and 52%-54%, respectively, were obtained. In comparison, decolorization percentages of 75%-79% were obtained using a consortium of C. mexicana and ACS. The same trend was observed for the decolorization of dyes at higher concentrations, but the potential for decolorization was low. The toxic azo dyes adversely affect the growth of microalgae and at high concentration 50 mg L-1 the growth rate inhibited to 50-60% as compared to the control. The natural textile wastewater was also treated with the same pattern and got promising results of decolorization (90%). Moreover, the removal of BOD (82%), COD (72%), TN (64%), and TP (63%) was observed with the consortium. The HPLC and GC-MS confirm dye biotransformation, revealing the emergence of new peaks and the generation of multiple metabolites with more superficial structures, such as N-hydroxy-aniline, naphthalene-1-ol, and sodium hydroxy naphthalene. This analysis demonstrates the potential of the C. mexicana and ACS consortium for efficient, eco-friendly bioremediation of textile azo dyes.
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Biodegradación Ambiental , Colorantes , Microalgas , Aguas del Alcantarillado , Industria Textil , Eliminación de Residuos Líquidos , Contaminantes Químicos del Agua , Colorantes/metabolismo , Colorantes/química , Aguas del Alcantarillado/química , Contaminantes Químicos del Agua/metabolismo , Microalgas/metabolismo , Eliminación de Residuos Líquidos/métodos , Aguas Residuales/química , Textiles , Compuestos Azo/metabolismoRESUMEN
Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine learning (ML) algorithm to predict sNEC using perinatal factors obtained from the national cohort registry of very low birth weight (VLBW) infants. Data were collected from the medical records of 16,385 VLBW infants registered in the Korean Neonatal Network (KNN). Infants who underwent surgical intervention were identified with sNEC, and infants who received medical treatment, with medical NEC (mNEC). We used 38 variables, including maternal, prenatal, and postnatal factors that were obtained within 1 week of birth, for training. A total of 1085 patients had NEC (654 with sNEC and 431 with mNEC). VLBW infants showed a higher incidence of sNEC at a lower gestational age (GA) (p < 0.001). Our proposed ensemble model showed an area under the receiver operating characteristic curve of 0.721 for sNEC prediction. Conclusion: Proposed ensemble model may help predict which infants with NEC are likely to develop sNEC. Through early prediction and prompt intervention, prognosis of sNEC may be improved. What is Known: ⢠Machine learning (ML)-based techniques have been employed in NEC research for prediction, diagnosis, and prognosis, with promising outcomes. ⢠While most studies have utilized abdominal radiographs and clinical manifestations of NEC as data sources, and have demonstrated their usefulness, they may prove weak in terms of early prediction. What is New: ⢠We analyzed the perinatal factors of VLBW infants acquired within 7 days of birth and used ML-based analysis to identify which infants with NEC are vulnerable to clinical deterioration and at high risk for surgical intervention using nationwide cohort data.
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Enterocolitis Necrotizante , Recién Nacido de muy Bajo Peso , Aprendizaje Automático , Humanos , Enterocolitis Necrotizante/diagnóstico , Enterocolitis Necrotizante/cirugía , Recién Nacido , Femenino , Masculino , República de Corea/epidemiología , Enfermedades del Prematuro/diagnóstico , Enfermedades del Prematuro/cirugía , Estudios de Cohortes , Edad Gestacional , Factores de Riesgo , Recien Nacido Prematuro , Estudios Retrospectivos , Sistema de Registros , Medición de Riesgo/métodosRESUMEN
Ferroptosis is an emerging and novel type of iron-dependent programmed cell death which is mainly caused by the excessive deposition of free intracellular iron in the brain cells. This deposited free iron exerts a ferroptosis pathway, resulting in lipid peroxidation (LiPr). There are mainly three ferroptosis pathways viz. iron metabolism-mediated cysteine/glutamate, and LiPr-mediated. Iron is required by the brain as a redox metal for several physiological activities. Due to the iron homeostasis balance disruption, the brain gets adversely affected which further causes neurodegenerative diseases (NDDs) like Parkinson's and Alzheimer's disease, strokes, and brain tumors like glioblastoma (GBS), and glioma. Nanotechnology has played an important role in the prevention and treatment of these NDDs. A synergistic effect of nanomaterials and ferroptosis could prove to be an effective and efficient approach in the field of nanomedicine. In the current review, the authors have highlighted all the latest research in the field of ferroptosis, specifically emphasizing on the role of major molecular key players and various mechanisms involved in the ferroptosis pathway. Moreover, here the authors have also addressed the correlation of ferroptosis with the pathophysiology of NDDs and theragnostic effect of ferroptosis and nanomaterials for the prevention and treatment of NDDs.
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Enfermedad de Alzheimer , Neoplasias Encefálicas , Ferroptosis , Nanoestructuras , Enfermedad de Parkinson , Humanos , Enfermedad de Parkinson/tratamiento farmacológico , Enfermedad de Alzheimer/tratamiento farmacológico , Neoplasias Encefálicas/tratamiento farmacológico , Hierro , Peroxidación de LípidoRESUMEN
To date, research on microbial fuel cells (MFCs) has. focused on the production of cost-effective, high-performance electrodes and catalysts. The present study focuses on the synthesis of silver nanoparticles (AgNPs) by Pseudomonas sp. and evaluates their role as an oxygen reduction reaction (ORR) catalyst in an MFC. Biogenic AgNPs were synthesized from Pseudomonas aeruginosa via facile hydrothermal synthesis. The physiochemical characterization of the biogenic AgNPs was conducted via scanning electron microscopy (SEM), X-ray diffraction (XRD), and UV-visible spectrum analysis. SEM micrographs showed a spherical cluster of AgNPs of 20-100 nm in size. The oxygen reduction reaction (ORR) ability of the biogenic AgNPs was studied using cyclic voltammetry (CV). The oxygen reduction peaks were observed at 0.43 V, 0.42 V, 0.410 V, and 0.39 V. Different concentrations of biogenic AgNPs (0.25-1.0 mg/cm2) were used as ORR catalysts at the cathode in the MFC. A steady increase in the power production was observed with increasing concentrations of biogenic AgNPs. Biogenic AgNPs loaded with 1.0 mg/cm2 exhibited the highest power density (PDmax) of 4.70 W/m3, which was approximately 26.30% higher than the PDmax of the sample loaded with 0.25 mg/cm2. The highest COD removal and Coulombic efficiency (CE) were also observed in biogenic AgNPs loaded with 1.0 mg/cm2 (83.8% and 11.7%, respectively). However, the opposite trend was observed in the internal resistance of the MFC. The lowest internal resistance was observed in a 1.0 mg/cm2 loading (87 Ω), which is attributed to the high oxygen reduction kinetics at the surface of the cathode by the biogenic AgNPs. The results of this study conclude that biogenic AgNPs are a cost-effective, high-performance ORR catalyst in MFCs.
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Introduction: Sustainable agriculture and meeting the world's food needs face considerable obstacles from abiotic stresses such as soil salinity and drought. This critical issue was addressed by our current study, which sought to uncover multi-trait bioinoculants from hostile ecosystems that could help mitigate salinity and drought stresses at the same time. Methods: The Bacillus subtilis ER-08 (BST) strain was isolated from the halotolerant plant Fagonia cretica which was collected from the Little Rann of Kachchh, India. Various biochemical and molecular approaches were applied for the detailed characterization of the BST isolate. Results and discussion: The BST isolate demonstrated notable plant growth-promoting qualities. Fenugreek seed biopriming was performed using the BST isolate. The effect of BST seed treatment on fenugreek developmental indices as well as abiotic alleviation was examined under greenhouse conditions. The BST produced 83.7 g ml-1 gibberellins (GA3) and 176.1 g ml-1 indole-3 acetic acid. Moreover, hydrogen cyanide, siderophore, exopolysaccharides (EPS), ammonia, cellulase, protease, pectinase, and chitinase were also produced by the BST strain. Interestingly, 52% of Fusarium oxysporum mycelial growth was suppressed by the BST isolate under in vitro conditions. Furthermore, BST isolates functioned well under several abiotic stress conditions, for instance, salinity (4 and 6 ds m-1), pH (5, 7, and 9), drought (PEG6000 at 10%, 20%, and 30%), and temperature (25°C, 35°C, 37°C, and 55°C). This study indicates that the BST strain might serve as an effective bio-inoculant for minimizing the detrimental effects of abiotic stresses.
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Dysbiosis of the gut microbiome is thought to be the developmental origins of the host's health and disease through the microbiota-gut-brain (MGB) axis: such as immune-mediated, metabolic, neurodegenerative, and neurodevelopmental diseases. Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common neurodevelopmental disorders, and growing evidence indicates the contribution of the gut microbiome changes and imbalances to these conditions, pointing to the importance of considering the MGB axis in their treatment. This review summarizes the general knowledge of gut microbial colonization and development in early life and its role in the pathogenesis of ASD/ADHD, highlighting a promising therapeutic approach for ASD/ADHD through modulation of the gut microbiome using psychobiotics (probiotics that positively affect neurological function and can be applied for the treatment of psychiatric diseases) and fecal microbial transplantation (FMT).
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Trastorno por Déficit de Atención con Hiperactividad , Trastorno del Espectro Autista , Trastorno Autístico , Microbioma Gastrointestinal , Microbiota , Humanos , Trastorno por Déficit de Atención con Hiperactividad/terapia , Trastorno del Espectro Autista/terapia , Trasplante de Microbiota FecalRESUMEN
INTRODUCTION: Prediction models assessing the mortality of very-low-birth-weight (VLBW) infants were confined to models using only pre- and perinatal variables. We aimed to construct a prediction model comprising multifactorial clinical events with data obtainable at various time points. METHODS: We included 15,790 (including 2,045 in-hospital deaths) VLBW infants born between 2013 and 2020 who were enrolled in the Korean Neonatal Network, a nationwide registry. In total, 53 prenatal and postnatal variables were sequentially added into the three discrete models stratified by hospital days: (1) within 24 h (TL-1d), (2) from day 2 to day 7 after birth (TL-7d), (3) from day 8 after birth to discharge from the neonatal intensive care unit (TL-dc). Each model predicted the mortality of VLBW infants within the affected period. Multilayer perception (MLP)-based network analysis was used for modeling, and ensemble analysis with traditional machine learning (ML) analysis was additionally applied. The performance of models was compared using the area under the receiver operating characteristic curve (AUROC) values. The Shapley method was applied to reveal the contribution of each variable. RESULTS: Overall, the in-hospital mortality was 13.0% (1.2% in TL-1d, 4.1% in TL-7d, and 7.7% in TL-dc). Our MLP-based mortality prediction model combined with ML ensemble analysis had AUROC values of 0.932 (TL-1d), 0.973 (TL-7d), and 0.950 (TL-dc), respectively, outperforming traditional ML analysis in each timeline. Birth weight and gestational age were constant and significant risk factors, whereas the impact of the other variables varied. CONCLUSION: The findings of the study suggest that our MLP-based models could be applied in predicting in-hospital mortality for high-risk VLBW infants. We highlight that mortality prediction should be customized according to the timing of occurrence.
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Mortalidad Infantil , Recién Nacido de muy Bajo Peso , Recién Nacido , Lactante , Embarazo , Femenino , Humanos , Estudios de Cohortes , Peso al Nacer , Factores de RiesgoRESUMEN
Heterocyclic compounds are significant lead drug candidates based on their various structure-activity relationships (SAR), and their use in pharmaceutics is constantly developing. Benzimidazole (BnZ) is synthesized by a condensation reaction between benzene and imidazole. The BnZ structure consists of two nitrogen atoms embedded in a five-membered imide ring which is fused with a benzene ring. This review examines the conventional and green synthesis of metallic and non-metallic BnZ and their derivatives, which have several potential SARs, along with a wide range of pharmacological properties, including anti-cancer, anti-inflammatory, anti-microbial, anti-tubercular, and anti-protozoal properties. These compounds have been proven by pharmacological investigations to be efficient against different strains of microbes. Therefore, in this review, the structural variations of BnZ are listed along with various applications, predominantly related to their biological activities.
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Antiinfecciosos , Antiinflamatorios , Bencimidazoles , Bencimidazoles/síntesis química , Bencimidazoles/química , Bencimidazoles/farmacología , Relación Estructura-Actividad , Benceno/química , Imidazoles/química , Antiinflamatorios/síntesis química , Antiinflamatorios/química , Antiinflamatorios/farmacología , Catálisis , Metales/químicaRESUMEN
Introduction: The aim of this study is to develop an enhanced machine learning-based prediction models for bronchopulmonary dysplasia (BPD) and its severity through a two-stage approach integrated with the duration of respiratory support (RSd) using prenatal and early postnatal variables from a nationwide very low birth weight (VLBW) infant cohort. Methods: We included 16,384 VLBW infants admitted to the neonatal intensive care unit (NICU) of the Korean Neonatal Network (KNN), a nationwide VLBW infant registry (2013-2020). Overall, 45 prenatal and early perinatal clinical variables were selected. A multilayer perceptron (MLP)-based network analysis, which was recently introduced to predict diseases in preterm infants, was used for modeling and a stepwise approach. Additionally, we applied a complementary MLP network and established new BPD prediction models (PMbpd). The performances of the models were compared using the area under the receiver operating characteristic curve (AUROC) values. The Shapley method was used to determine the contribution of each variable. Results: We included 11,177 VLBW infants (3,724 without BPD (BPD 0), 3,383 with mild BPD (BPD 1), 1,375 with moderate BPD (BPD 2), and 2,695 with severe BPD (BPD 3) cases). Compared to conventional machine learning (ML) models, our PMbpd and two-stage PMbpd with RSd (TS-PMbpd) model outperformed both binary (0 vs. 1,2,3; 0,1 vs. 2,3; 0,1,2 vs. 3) and each severity (0 vs. 1 vs. 2 vs. 3) prediction (AUROC = 0.895 and 0.897, 0.824 and 0.825, 0.828 and 0.823, 0.783, and 0.786, respectively). GA, birth weight, and patent ductus arteriosus (PDA) treatment were significant variables for the occurrence of BPD. Birth weight, low blood pressure, and intraventricular hemorrhage were significant for BPD ≥2, birth weight, low blood pressure, and PDA ligation for BPD ≥3. GA, birth weight, and pulmonary hypertension were the principal variables that predicted BPD severity in VLBW infants. Conclusions: We developed a new two-stage ML model reflecting crucial BPD indicators (RSd) and found significant clinical variables for the early prediction of BPD and its severity with high predictive accuracy. Our model can be used as an adjunctive predictive model in the practical NICU field.
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The antioxidant and anti-inflammatory properties of an aqueous natural extract obtained from Rosa sempervirens leaves were assessed. The ability of the extract to scavenge DPPH, â¢OH, and H2O2 radicals, chelate ferrous ions, reduce ferric ions, and protect ß-carotene-linoleic acid in emulsion from peroxidation was investigated in vitro. Furthermore, the anti-inflammatory activity of the extract was evaluated by measuring the stability of the membrane of human red blood cells against different hypotonic concentrations of NaCl and heat, as well as by inhibiting the denaturation of albumin. A high total phenolic content (278.38± 11.07 mg GAE/g) and flavonoid content (34.22± 0.12 mg QE /g) were found in the extract. The extract exhibited significant scavenging activity of DPPH (IC50 6.201 ± 0.126 µg/ ml), â¢OH (IC50 = 894.57 ± 21.18 µg/ml), and H2O2 (IC50= 107±09.58 µg/ml) radicals, and good antioxidant activity by chelating ferrous ions (IC50 = 2499.086 ± 28.267µg/ml), reducing ferric ions (IC50=141.33±2.34 µg/ml), exhibiting total antioxidant capacity (IC50 465.65 ± 9.71 µg/ml), and protecting ß-carotene-linoleic acid against peroxidation (I% = 90.05 ± 1.65% at 1000µg/ml). R. sempervirens displayed anti-inflammatory activity in aqueous extract by inhibiting heat-induced albumin denaturation and stabilizing the membrane of human red blood cells. It was suggested from the results that R. sempervirens aqueous extract could help prevent oxidative and inflammatory processes due to its good antioxidant and anti-inflammatory properties.
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Antioxidantes , Rosa , Humanos , Antioxidantes/química , Peróxido de Hidrógeno/química , Ácido Linoleico , beta Caroteno/análisis , Extractos Vegetales/química , Hojas de la Planta/química , Antiinflamatorios/farmacologíaRESUMEN
This study aimed to evaluate the difference in gut microbiomes between preterm and term infants using third-generation long-read sequencing (Oxford Nanopore Technologies, ONT) compared with an established gold standard, Illumina (second-generation short-read sequencing). A total of 69 fecal samples from 51 term (T) and preterm (P) infants were collected at 7 and 28 days of life. Gut colonization profiling was performed by 16S rRNA gene sequencing using ONT. We used Illumina to validate and compare the patterns in 13 neonates. Using bioinformatic analysis, we identified features that differed between P and T. Both T1 and P1 microbiomes were dominated by Firmicutes (Staphylococcus and Enterococcus), whereas sequentially showed dominant transitions to Lactobacillus (p < 0.001) and Streptococcus in T2 (p = 0.001), and pathogenic bacteria (Klebsiella) in P2 (p = 0.001). The abundance of beneficial bacteria (Bifidobacterium and Lactobacillus) increased in T2 (p = 0.026 and p < 0.001, respectively). These assignments were correlated with the abundance at the species-level. Bacterial α-diversity increased in T (p = 0.005) but not in P (p = 0.156), and P2 showed distinct ß-diversity clustering than T2 (p = 0.001). The ONT reliably identified pathogenic bacteria at the genus level, and taxonomic profiles were comparable to those identified by Illumina at the genus level. This study shows that ONT and Illumina are highly correlated. P and T had different microbiome profiles, and the α- and ß-diversity varied. ONT sequencing has potential for pathogen detection in neonates in clinical settings.
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The preeminence of sulfonamide drug resistance genes in food waste (FW) and the increased utilization of high-strength organic FW in anaerobic digestion (AD) to enhance methane production have raised severe public health concerns in wastewater treatment plants worldwide. In this regard, the dissemination patterns of different sulfonamide resistance genes (sul1 and sul2) and their impact on the digester core microbiota during AD of FW leachate (FWL) were evaluated. The presence of various sulfonamide antibiotics (SAs) in FWL digesters improved the final methane yield by 37 % during AD compared with FWL digesters without SAs. Microbial population shifts towards hydrolytic, acidogenic, and acetogenic bacteria in the phyla Actinobacteriota, Bacteroidota, Chloroflexi, Firmicutes, Proteobacteria, and Synergistota occurred due to SA induced substrate digestion and absorption through active transport; butanoate, propanoate, and pyruvate metabolism; glycolysis; gluconeogenesis; the citrate cycle; and pentose phosphate pathway. The initial dominance of Methanosaeta (89-96 %) declined to 47-53 % as AD progressed and shifted towards Methanosarcina (40 %) in digesters with the highest SA concentrations at the end of AD. Dissemination of sul1 depended on class 1 integron gene (intl1)-based horizontal gene transfer to pathogenic members of Chloroflexi, Firmicutes, and Patescibacteria, whereas sul2 was transmitted to Synergistota independent of intl1. Low susceptibility and ability to utilize SAs during methanogenesis shielded methanogenic archaea against selection pressure, thus preventing them from interacting with sul or intl1 genes, thereby minimizing the risk of antibiotic resistance development. The observed emergence of cationic antimicrobial peptide, vancomycin, and ß-lactam resistance in the core microbiota during AD of FWL in the presence of SAs suggests that multidrug resistance caused by bacterial transformation could lead to an increase in the environmental resistome through wastewater sludge treatment.
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Chloroflexi , Microbiota , Eliminación de Residuos , Anaerobiosis , Alimentos , Microbiota/genética , Aguas del Alcantarillado/microbiología , Bacterias/metabolismo , Sulfanilamida , Antibacterianos/metabolismo , Firmicutes , Metano/metabolismo , Reactores BiológicosRESUMEN
In the untact COVID-19 era, the feasibility of a noncontact, impulse-radio ultrawideband (IR-UWB) radar sensor has important medical implications. Premature birth is a major risk factor for brain injury and developmental delay; therefore, early intervention is crucial for potentially achieving better developmental outcomes. Early detection and screening tests in infancy are limited to the quantification of differences between normal and spastic movements. This study investigated the quantified asymmetry in the general movements of an infant with hydrocephalus and proposes IR-UWB radar as a novel, early screening tool for developmental delay. To support this state-of-the-art technology, data from actigraphy and video camcorder recordings were adopted simultaneously to compare relevant time series as the infant grew. The data from the three different methods were highly concordant; specifically, the ρz values comparing radar and actigraphy, which served as the reference for measuring movements, showed excellent agreement, with values of 0.66 on the left and 0.56 on the right. The total amount of movement measured by radar over time increased overall; movements were almost dominant on the left at first (75.2% of total movements), but following shunt surgery, the frequency of movement on both sides was similar (54.8% of total movements). As the hydrocephalus improved, the lateralization of movement on radar began to coincide with the clinical features. These results support the important complementary role of this radar system in predicting motor disorders very early in life.
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Cystic periventricular leukomalacia (cPVL) is a major brain injury involving periventricular white matter that leads to neurodevelopmental impairment in very-low-birth weight (VLBW) infants. We investigated the neurodevelopmental outcomes (motor, cognition, visual, and hearing) of 5734 VLBW infants born between 2013 and 2019 and enrolled in the Korean Neonatal Network. Cranial ultrasound results were stratified by the presence of cPVL and severity of intraventricular hemorrhage (IVH) (no, low-grade [I/II], high-grade [III]). Neurodevelopmental impairment was evaluated using cerebral palsy for motor and Bayley Scales of Infant Development for cognition. cPVL was associated with motor, cognitive, and visual impairments in those without IVH and with low-grade IVH in pairwise comparisons (Cochran−Mantel−Haenszel p < 0.001). Conversely, cPVL was non-significantly correlated with cognitive impairment in high-grade IVH. In regression models adjusted for neonatal variables, isolated cPVL was strongly associated with motor (22.04; 11.39−42.63) and cognitive (3.10; 1.54−6.22) impairments. This study underlines the overall considerable significance of cPVL on NDI with divergent impacts depending on the severity of IVH and developmental indices.
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Physical fatigue can be assessed using heart rate variability (HRV). We measured HRV at rest and in a fatigued state using impulse-radio ultra wideband (IR-UWB) radar in a noncontact fashion and compared the measurements with those obtained using electrocardiography (ECG) to assess the reliability and validity of the radar measurements. HRV was measured in 15 subjects using radar and ECG simultaneously before (rest for 10 min before exercise) and after a 20-min exercise session (fatigue level 1 for 0-9 min; fatigue level 2 for 10-19 min; recovery for ≥ 20 min after exercise). HRV was analysed in the frequency domain, including the low-frequency component (LF), high-frequency component (HF) and LF/HF ratio. The LF/HF ratio measured using radar highly agreed with that measured using ECG during rest (ICC = 0.807), fatigue-1 (ICC = 0.712), fatigue-2 (ICC = 0.741) and recovery (ICC = 0.764) in analyses using intraclass correlation coefficients (ICCs). The change pattern in the LH/HF ratios during the experiment was similar between radar and ECG. The subject's body fat percentage was linearly associated with the time to recovery from physical fatigue (R2 = 0.96, p < 0.001). Our results demonstrated that fatigue and rest states can be distinguished accurately based on HRV measurements using IR-UWB radar in a noncontact fashion.
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Radar , Procesamiento de Señales Asistido por Computador , Electrocardiografía , Fatiga/diagnóstico , Frecuencia Cardíaca , Humanos , Reproducibilidad de los ResultadosRESUMEN
Intestinal perforation (IP) in preterm infants is a life-threatening condition that may result in serious complications and increased mortality. Early Prediction of IP in infants is important, but challenging due to its multifactorial and complex nature of the disease. Thus, there are no reliable tools to predict IP in infants. In this study, we developed new machine learning (ML) models for predicting IP in very low birth weight (VLBW) infants and compared their performance to that of classic ML methods. We developed artificial neural networks (ANNs) using VLBW infant data from a nationwide cohort and prospective web-based registry. The new ANN models, which outperformed all other classic ML methods, showed an area under the receiver operating characteristic curve (AUROC) of 0.8832 for predicting IP associated with necrotizing enterocolitis (NEC-IP) and 0.8797 for spontaneous IP (SIP). We tested these algorithms using patient data from our institution, which were not included in the training dataset, and obtained an AUROC of 1.0000 for NEC-IP and 0.9364 for SIP. NEC-IP and SIP in VLBW infants can be predicted at an excellent performance level with these newly developed ML models. https://github.com/kdhRick2222/Early-Prediction-of-Intestinal-Perforation-in-Preterm-Infants .