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ACS Omega Jun 2024Bio-oil production from rice husk, an abundant agricultural residue, has gained significant attention as a sustainable and renewable energy source. The current research...
Bio-oil production from rice husk, an abundant agricultural residue, has gained significant attention as a sustainable and renewable energy source. The current research aims to employ artificial neural network (ANN) and support vector machine (SVM) modeling techniques for the optimization of operating parameters for bio-oil extracted from rice husk ash (RHA) through pyrolysis. ANN and SVM methods are employed to model and optimize the operational conditions, including temperature, heating rate, and feedstock particle size, to enhance the yield and quality of bio-oil. Additionally, ANN modeling is utilized to create a predictive model for bio-oil properties, allowing for the efficient optimization of pyrolysis conditions. This research provides valuable insights into the production and properties of bio-oil from RHA. By harnessing the capabilities of ANN and SVM, this research not only aids in understanding the intricate relationships between process variables and bio-oil properties but also provides a means to systematically enhance the production process. The predictive results obtained from the ANN were found to be good when compared with the SVM. Several models with different numbers of neurons have been trained with different transfer functions. values for the training, validation, and test phases are around 1.0, i.e., 0.9981, 0.9976, and 0.9978, respectively. The overall -value was 0.9960 for the proposed network. The findings were considered acceptable, as the overall -value was close to 1.0. The optimized operational parameters contribute to the efficient conversion of RHA into bio-oil, thereby promoting the use of this sustainable resource for renewable energy production. This approach aligns with the growing emphasis on reducing the environmental impact of traditional fossil fuels and advancing the utilization of alternative and environmentally friendly energy sources.
PubMed: 38911793
DOI: 10.1021/acsomega.4c03131 -
ACS Omega Jun 2024Antimicrobial resistance has increased rapidly, causing daunting morbidity and mortality rates worldwide. Antimicrobial peptides (AMPs) have emerged as promising...
Antimicrobial resistance has increased rapidly, causing daunting morbidity and mortality rates worldwide. Antimicrobial peptides (AMPs) have emerged as promising alternatives to traditional antibiotics due to their broad range of targets and low tendency to elicit resistance. However, potent antimicrobial activity is often accompanied by excessive cytotoxicity toward host cells, leading to a halt in AMP therapeutic development. Here, we present multivariate analyses that correlate 28 peptide properties to the activity and toxicity of 46 diverse African-derived AMPs and identify the negative lipophilicity of polar residues as an essential physiochemical property for selective antimicrobial activity. Twenty-seven active AMPs are identified, of which the majority are of scorpion or frog origin. Of these, thirteen are novel with no previously reported activities. Principal component analysis and quantitative structure-activity relationships (QSAR) reveal that overall hydrophobicity, lipophilicity, and residue side chain surface area affect the antimicrobial and cytotoxic activity of an AMP. This has been well documented previously, but the present QSAR analysis additionally reveals that a decrease in the lipophilicity, contributed by those amino acids classified as polar, confers selectivity for a peptide to pathogen over mammalian cells. Furthermore, an increase in overall peptide charge aids selectivity toward Gram-negative bacteria and fungi, while selectivity toward Gram-positive bacteria is obtained through an increased number of small lipophilic residues. Finally, a conservative increase in peptide size in terms of sequence length and molecular weight also contributes to improved activity without affecting toxicity. Our findings suggest a novel approach for the rational design or modification of existing AMPs to increase pathogen selectivity and enhance therapeutic potential.
PubMed: 38911757
DOI: 10.1021/acsomega.4c01277 -
ACS Omega Jun 2024Pyrolytic oil is currently in its early stages of production and distribution but has the potential to grow into a significant renewable energy source. It may be...
Pyrolytic oil is currently in its early stages of production and distribution but has the potential to grow into a significant renewable energy source. It may be processed into a variety of useful substances, including chemicals, and used for heating, transportation, and energy production. The present investigation involves the production and characterization of pyrolytic oil from areca nut husk (ANH), with and without ZSM-5. The pyrolysis experiment was conducted in a semibatch tubular reactor at 600 °C and a heating rate of 80 °C min using ZSM-5 at 20 wt %. The pyrolytic oil was examined via elemental analysis, viscosity, density, moisture content, GC-MS, FTIR, higher heating value (HHV), and ash content. The analysis of kinetics verified that the activation energy rises in proportion to the conversion rate. Additionally, employing ZSM-5 in catalytic pyrolysis at 20 wt % boosted the yield of pyrolytic oil by 11% compared to thermal pyrolysis. Employing ZSM-5 at 20 wt % resulted in a decrease in viscosity, oxygen content, and density by approximately 43.40 cSt, 15.20%, and 168 MJ kg1, respectively. Moreover, it led to an increase in higher heating value (HHV) and carbon content by 11.71 MJ kg and 14.06%, respectively. An FTIR study of pyrolytic oil revealed the occurrence of hydrocarbons, aromatics, phenols, alcohols, and oxygenated chemicals. Moreover, GC-MS analysis indicated a significant increase in hydrocarbons (10.31%) and a decrease in phenols (2.36%), acids (6.38%), and oxygenated compounds with the introduction of the catalyst. Consequently, it can be inferred that utilizing ZSM-5 at 20 wt % during the pyrolysis of ANH aids in enhancing both the yield and characteristics of the resulting pyrolysis oil.
PubMed: 38911756
DOI: 10.1021/acsomega.3c10184 -
Annals of Translational Medicine Jun 2024There is a limited research on predictive models of fat mass ratio (FMR) in people living with human immunodeficiency virus (HIV) (PWH). This study aimed to develop...
BACKGROUND
There is a limited research on predictive models of fat mass ratio (FMR) in people living with human immunodeficiency virus (HIV) (PWH). This study aimed to develop models considering anthropometric and health-related factors to predict and validate FMR in PWH regardless of sex.
METHODS
One hundred and six Brazilian PWH (46.4±9.8 years) were evaluated for body composition using dual-energy X-ray absorptiometry (DXA), body circumference (BC), and skinfold thicknesses (SKs). FMR predictive models were developed using stepwise linear regression, and their agreement with DXA was assessed using Bland-Altman plots. Cross-validation was performed using the predicted residual error sum of squares (PRESS) method.
RESULTS
Six FMR estimation models were developed for PWH, with adjusted R ranging from 0.43 to 0.72, standard error of the estimate (SEE) from 0.16% to 0.22%, and 95% confidence interval (CI) from 1.03 to 1.15. Model 6, including thigh SK, waist BC, therapy duration, subscapular SK, education years, and abdominal SK, exhibited the highest determination power (R adjusted 0.72, SEE 0.16%, and 95% CI: 1.06-1.15). The agreement between DXA-based FMR and predictive models showed minimal bias (-0.03 to +0.04) and narrower limits of agreement, particularly for the top-performing model (-0.33 to +0.30). Model 6 exhibited a high adjusted QPRESS (0.70) and low SPRESS (0.17).
CONCLUSIONS
Our predictive models advance the study of body composition in PWH by consolidating the use of anthropometry for diagnosing and monitoring lipodystrophy regardless of sex.
PubMed: 38911564
DOI: 10.21037/atm-23-1946 -
SAGE Open Medicine 2024Ambulatory mobility aids are several devices the elderly may use in order to improve their walking pattern, balance, or safety while mobilizing independently.
INTRODUCTION
Ambulatory mobility aids are several devices the elderly may use in order to improve their walking pattern, balance, or safety while mobilizing independently.
OBJECTIVES
To assess the effect of ambulatory mobility aid devices on cardiovascular parameters, walking speed, perceived exertion, and balance of older adult men.
METHODS
A sample of 156 old men was studied. Data were obtained through measurement of the participants' walking speed (distance covered/second), cardiovascular parameters (blood pressure), perceived exertion (difficulty or ease in breathing), and balance (ease in standing) after walking with and without the selected walking aid devices. Analysis was done to compare the effect of the walking aid devices on the selected dependent variables.
RESULTS
Results showed ambulation with mobility aid devices resulted in increase in the heart rate and blood pressure with the greatest increase observed when walking with Zimmer frame. Ambulation with mobility aid devices resulted in decrease of the walking speed of the participants when compared to ambulation without devices. Perceived exertion of participants after using Zimmer frame and walking cane was within 4.06 ± 1.35 and 3.98 ± 1.26, respectively, as opposed to 3.08 ± 0.73 after ambulation without aid. Use of Zimmer frame provided enough balance for participants.
CONCLUSION
Ambulatory mobility devices caused difference in cardiovascular parameters when compared to ambulation at rest and without aid. It was recommended that selection of ambulatory mobility aid devices should depend on objective mobility assessments and periodical re-evaluation to ensure that it suits a person's functional requirements and physical capabilities.
PubMed: 38911443
DOI: 10.1177/20503121241262250 -
HIV/AIDS (Auckland, N.Z.) 2024Antiretroviral therapy (ART) adherence is crucial for virological suppression and positive treatment outcomes among people living with HIV (PLHIV), but remains a...
BACKGROUND
Antiretroviral therapy (ART) adherence is crucial for virological suppression and positive treatment outcomes among people living with HIV (PLHIV), but remains a challenge in ensuring patients achieve and sustain viral load suppression. Despite the recommended use of digital tools medications uptake reminders, the contribution of forgetting to take medication is unknown. This study investigated the contribution of forgetting to take medication on the total missed medication and its effects on detectable viral load (VL).
METHODS
This mixed-method research was conducted among children, adolescents, pregnant, and breastfeeding women living with HIV on ART in northern Tanzania. Forgetting to take medication constituted reporting to have missed medication due to forgetfulness. A multivariable logistic regression model was used to estimate the adjusted odds ratio (AOR) with a 95% confidence interval (CI) to determine the contribution of forgetting medication intakes on total missed medication and other factors associated with having a detectable VL.
RESULTS
Of 427 respondents, 33.3% were children, 33.4% adolescents, and 33.3% pregnant and breastfeeding women, whose median age (interquartile range) was 9 (7-12), 18 (16-18), and 31 (27-36) years, respectively. Ninety-two (22.3%) reported missing medication over the past month, of which 72 (17.9%) was due to forgetting. Forgetting to take medication (AOR: 1.75 95% CI: 1.01-3.06) and being on second-line regimen (AOR: 2.89 95% CI: 1.50-5.55) increased the chances of a detectable VL, while females had lower chances of detectable VL (AOR: 0.62 95% CI: 0.41-0.98). The themes on the reasons for forgetting to take medication from qualitative results included being busy with work and the importance of reminders.
CONCLUSION
Forgetting to take medication is common among PLHIV and an important predictor of a detectable VL. This calls for the use of automated short message services (SMS) reminders or Digital Adherence Tools with reminders to improve and promote good ART adherence among PLHIV.
PubMed: 38911143
DOI: 10.2147/HIV.S452875 -
Journal of Oral Microbiology 2024Healthcare settings may amplify transmission of respiratory pathogens, however empirical evidence is lacking. We aimed to describe the spectrum and distribution of...
BACKGROUND
Healthcare settings may amplify transmission of respiratory pathogens, however empirical evidence is lacking. We aimed to describe the spectrum and distribution of respiratory pathogens among healthcare workers in eastern China.
METHODS
Healthcare workers were recruited from October 2020 to November 2021 in Jiangsu province. Participants were interviewed regarding demographic and hospital-based protective measures. Thirty-seven common respiratory pathogens were tested using real-time PCR/RT-PCR (Probe qPCR). The role of demographic and hospital-based protective measures on pathogens colonization using multivariable logistic regression models.
RESULTS
Among 316 enrolled healthcare workers, a total of 21 pathogens were detected. In total, 212 (67.1%) healthcare workers had at least one respiratory pathogen; 195 (61.7%) and 70 (22.2%) with a bacterial and viral pathogen. The most commonly detected pathogen was streptococcus pneumoniae (47.5%) followed by influenzae (21.2%). One hundred and five (33.2%) healthcare workers with copathogens had at least two respiratory pathogens. Both bacterial and viral colonization were more common in 2020 compared to 2021. A decreased risk of colonization was seen in participants with infection prevention and control training and suitable hand hygiene.
CONCLUSIONS
Colonization of respiratory pathogens in healthcare workers from eastern China was high. Differential risk was impacted only by hospital-based protective measures and not demographic factors.
PubMed: 38910869
DOI: 10.1080/20002297.2024.2365965 -
Pediatric Investigation Jun 2024Systemic lupus erythematosus (SLE) is a diffuse connective tissue disease with complex clinical manifestations and prolonged course. The early diagnosis and condition...
IMPORTANCE
Systemic lupus erythematosus (SLE) is a diffuse connective tissue disease with complex clinical manifestations and prolonged course. The early diagnosis and condition monitoring of SLE are crucial to disease prognosis.
OBJECTIVE
To assess the diagnostic value of long noncoding RNA (lncRNA) nuclear enriched abundant transcript 1 (NEAT1) in childhood-onset SLE (cSLE).
METHODS
Fifty-seven children diagnosed with SLE, 40 children diagnosed with juvenile idiopathic arthritis (JIA), and 40 healthy children were included. Peripheral blood samples from each patient were collected. A quantitative polymerase chain reaction was used to confirm the expression of lncNEAT1_1 and lncNEAT1_2 in peripheral blood. Associations among parameters were analyzed using the Mann-Whitney test or independent sample -test.
RESULTS
The expression of both lncNEAT1_1 and lncNEAT1_2 in patients with cSLE were significantly higher than that of healthy control and patients with JIA. Receiver operating characteristic curves revealed an area under the curve (AUC) of 0.633 (95% confidence interval [CI], 0.524-0.742; = 0.024) for lncNEAT1_1. The AUC of lncNEAT1_2 was 0.812 (95% CI, 0.727-0.897; < 0.0001) to discriminate individuals with cSLE from health control and children with JIA with a sensitivity of 0.622 and a specificity of 0.925. Moreover, lncNEAT1_2 expression was higher in patients with cSLE presenting with fever, lupus nephritis, elevated erythrocyte sedimentation rate, active disease activity, and decreased C3 level, compared with those without these conditions. However, no similar correlation was observed for lncNEAT1_1.
INTERPRETATION
The expression of lncNEAT1_2 was significantly elevated in children with SLE, especially those with fever, renal involvement, and low C3 levels. These findings suggest that lncNEAT1_2 may represent a potential biomarker for cSLE.
PubMed: 38910848
DOI: 10.1002/ped4.12413 -
Cureus May 2024The development of Hodgkin's lymphoma (HL) is a known complication in patients with human immunodeficiency virus (HIV) infection. Extranodal involvement, specifically...
The development of Hodgkin's lymphoma (HL) is a known complication in patients with human immunodeficiency virus (HIV) infection. Extranodal involvement, specifically primary bone marrow Hodgkin's lymphoma (PBMHL) is a rare manifestation that has been reported in HIV-positive patients and may represent a distinct entity from HIV-associated HL. We present a case of PBMHL presenting with hemophagocytic lymphohistiocytosis (HLH) in an HIV-positive patient. The 55-year-old male with HIV/AIDS presented with abdominal pain, diarrhea, and fever, leading to hospital admission. Despite initial treatment, he deteriorated, prompting re-admission and investigation revealing pancytopenia and elevated inflammatory markers, suggestive of HLH. Subsequent bone marrow biopsy unexpectedly revealed PBMHL. Treatment with HLH-directed therapy and the HLH-94 protocol resulted in significant clinical improvement. This case underscores the importance of recognizing atypical lymphoproliferative presentations in HIV/AIDS patients and the need for interdisciplinary collaboration in complex cases.
PubMed: 38910743
DOI: 10.7759/cureus.60864 -
Clinics in Dermatology Jun 2024Artificial Intelligence (AI) has evolved to become a significant force in various domains, including medicine. We explore the role of AI in pathology, with a specific...
Artificial Intelligence (AI) has evolved to become a significant force in various domains, including medicine. We explore the role of AI in pathology, with a specific focus on dermatopathology and neoplastic dermatopathology. AI, encompassing Machine Learning (ML) and Deep Learning (DL), has demonstrated its potential in tasks ranging from diagnostic applications on Whole Slide Imaging (WSI) to predictive and prognostic functions in skin pathology. In dermatopathology, studies have assessed AI's ability to identify skin lesions, classify melanomas, and improve diagnostic accuracy. Results indicate that AI, particularly Convolutional Neural Networks (CNNs), can outperform human pathologists in terms of sensitivity and specificity. Moreover, AI aids in predicting disease outcomes, identifying aggressive tumors, and differentiating between various skin conditions. Neoplastic dermatopathology showcases AI's prowess in classifying melanocytic lesions, discriminating between melanomas and nevi, and aiding dermatopathologists in making accurate diagnoses. Studies emphasize the reproducibility and diagnostic aid that AI provides, especially in challenging cases. In inflammatory and lymphoproliferative dermatopathology, limited research exists, but studies show attempts to use AI to differentiate conditions like Mycosis Fungoides and eczema. While some results are promising, further exploration is needed in these areas. We highlight the extraordinary interest AI has garnered in the scientific community and its potential to assist clinicians and pathologists. Despite the advancements, we have stress edthe importance of collaboration between medical professionals, computer scientists, bioinformaticians, and engineers to harness AI's benefits while acknowledging its limitations and risks. The integration of AI into dermatopathology holds great promise, positioning it as a valuable tool rather than as a replacement for human expertise.
PubMed: 38909860
DOI: 10.1016/j.clindermatol.2024.06.010