Miracle-dz/UniFAR-FTUs huggingface dataset:
LightMixer: A novel lightweight convolutional neural network for tomato disease detection

Tomatoes are among the very important crops grown worldwide. However, tomato diseases can harm the health of tomato plants during growth and reduce tomato yields over large areas. The development of computer vision technology offers the prospect of solving this problem. However, traditional deep learning algorithms require a high computational cost and several parameters. Therefore, a lightweight tomato leaf disease identification model called LightMixer was designed in this study. The LightMixer model comprises a depth convolution with a Phish module and a light residual module. Depth convolution with the Phish module represents a lightweight convolution module designed to splice nonlinear activation functions with depth convolution as the backbone; it also focuses on lightweight convolutional feature extraction to facilitate deep feature fusion. The light residual module was built based on lightweight residual blocks to accelerate the computational efficiency of the entire network architecture and reduce the information loss of disease features. Experimental results show that the proposed LightMixer model achieved 99.3% accuracy on public datasets while requiring only 1.5 M parameters, an improvement over other classical convolutional neural network and lightweight models, and can be used for automatic tomato leaf disease identification on mobile devices.
Analysis of solar activity conditions during periods of El Niño events

The occurrence of El Nino events is analysed in relation to solar activity by considering solar activity conditions (such as sunspot numbers and their gradients) during which the events occurred. Most of the El Nino events are found to occur at small negative sunspot gradients and low sunspot numbers. The El Nino events are also found to be clustered within 1 year after the maximum rate of disappearance of sunspots
Building the case for mitochondrial transplantation as an anti-aging cardiovascular therapy

Mitochondrial dysfunction is a common denominator in both biological aging and cardiovascular disease (CVD) pathology. Understanding the protagonist role of mitochondria in the respective and independent progressions of CVD and biological aging will unravel the synergistic relationship between biological aging and CVD. Moreover, the successful development and implementation of therapies that can simultaneously benefit mitochondria of multiple cell types, will be transformational in curtailing pathologies and mortality in the elderly, including CVD. Several works have compared the status of mitochondria in vascular endothelial cells (ECs) and vascular smooth muscle cells (VSMCs) in CVD dependent context. However, fewer studies have cataloged the aging-associated changes in vascular mitochondria, independent of CVD. This mini review will focus on the present evidence related to mitochondrial dysfunction in vascular aging independent of CVD. Additionally, we discuss the feasibility of restoring mitochondrial function in the aged cardiovascular system through mitochondrial transfer.
A scoping review of maternal health among resettled refugee women in the United States

Background Globally, refugee women continue to face higher maternity-related risks from preventable complications during pregnancy and childbirth, partly due to high health care costs, unfamiliarity with the healthcare system, language barriers, and discrimination. Nevertheless, there is still a paucity of literature that evaluates the available evidence in the US. This scoping review delineated the body of literature on maternal health among refugee women resettled in the US in order to identify knowledge gaps in the literature and highlight future research priorities and directions for maternal health promotion. Methods Electronic databases were searched in PubMed, CINAHL, PsycINFO, and EMBASE from inception through July 2021. We included all peer-reviewed study designs; qualitative, quantitative, and mixed method if they reported on refugee women's perinatal health experiences and outcomes in the US. Results A total of 2,288 records were identified, with 29 articles meeting the inclusion criteria. Refugee women tend to initiate prenatal care late and have fewer prenatal care visits compared to women born in the US. Some of them were reluctant to get obstetric interventions such as labor induction and cesarean delivery. Despite numerous risk factors, refugee women had generally better maternal health outcomes. Studies have also highlighted the importance of health care providers' cultural competency and sensitivity, as well as the potential role of community health workers as a bridge between refugee women and health care providers. Conclusions The scoping review emphasizes the need for early prenatal care initiation and more frequent prenatal care visits among refugee women. Furthermore, more needs to be done to mitigate resistance to obstetric interventions and mistrust. The mechanism by which healthy migrant effects occur could be better understood, allowing protective factors to be maintained throughout the resettlement and acculturation process. The scoping review identifies critical gaps in the literature, such as the underrepresentation of different ethnic groups of refugee women in refugee maternal studies in the US. Since this invisibility may indicate unspoken and unaddressed needs, more attention should be paid to underrepresented and understudied groups of refugee women in order to achieve health equity for all.
Inhibition of AcrAB-TolC enhances antimicrobial activity of phytochemicals in Pectobacterium brasiliense

Introduction The eons-long co-evolvement of plants and bacteria led to a plethora of interactions between the two kingdoms, in which bacterial pathogenicity is counteracted by plant-derived antimicrobial defense molecules. In return, efflux pumps (EP) form part of the resistance mechanism employed by bacteria to permit their survival in this hostile chemical environment. In this work we study the effect of combinations of efflux pump inhibitors (EPIs) and plant-derived phytochemicals on bacterial activity using Pectobacteriun brasiliense 1692 (Pb1692) as a model system. Methods We measured the minimal inhibitory concentration (MIC) of two phytochemicals, phloretin (Pht) and naringenin (Nar), and of one common antibiotic ciprofloxacin (Cip), either alone or in combinations with two known inhibitors of the AcrB EP of Escherichia coli, a close homolog of the AcrAB-TolC EP of Pb1692. In addition, we also measured the expression of genes encoding for the EP, under similar conditions. Results Using the FICI equation, we observed synergism between the EPIs and the phytochemicals, but not between the EPIs and the antibiotic, suggesting that EP inhibition potentiated the antimicrobial activity of the plant derived compounds, but not of Cip. Docking simulations were successfully used to rationalize these experimental results. Discussion Our findings suggest that AcrAB-TolC plays an important role in survival and fitness of Pb1692 in the plant environment and that its inhibition is a viable strategy for controlling bacterial pathogenicity.
Feasibility, effectiveness and safety of self-management in pulmonary rehabilitation: a study protocol using a hybrid type 1 effectiveness-implementation design

Background As population ageing accelerates worldwide, chronic diseases will place an increasing burden on society and healthcare systems. Self-management interventions may become a key strategy for addressing chronic disease burden and healthcare costs, also in pulmonary rehabilitation (PR). One of the challenges here is long-term adherence. Understanding the level of adherence to PR may help inform clinical decision-making to focus more on self-management and less on clinical supervision. For this reason, a prediction model (PATCH) was developed. The presented protocol concerns a study that aims 1. to evaluate the safety and effectiveness of self-management within pulmonary rehabilitation (PR) on health outcomes in patients with chronic obstructive pulmonary disease (COPD), 2. to evaluate the predictive validity of the PATCH tool, and 3. to evaluate feasibility and acceptability of self-management and the PATCH tool by patients and physiotherapists. Methods and analysis This is a protocol of a hybrid type 1 effectiveness-implementation design, performed in primary physiotherapy practices in The Netherlands. The aim is to include 108 patients with COPD who have already followed PR for at least six weeks (maintenance stage of PR). According to the Dutch KNGF Guideline COPD, physiotherapists should reduce the number of supervised treatments after the maintenance phase and support self-management. In practice, this does not (always) happen. This protocol is based on implementing guideline advice: clinical supervision will be halved but patients are stimulated to engage in self-management by exercising unsupervised, leading to no change in the total planned exercise frequency. During the supervised sessions physiotherapists will assess and stimulate self-management. At baseline, and after 3, 6, 9 and 12 months, health outcomes (including adherence) will be evaluated as the primary outcome of this study. At each measurement, the physiotherapist will decide on the basis of individual scores whether the patient needs more clinical supervision or not. Secondary outcomes are the discriminatory power of the PATCH tool (can patients be correctly classified as adherent or non-adherent), and feasibility and acceptability of self-management and the PATCH tool by patients and physiotherapists. Questionnaires and semi-structured interviews will be used for assessment of the outcomes. Trial registration number: METc 2023/074.
Prediction of clinical response to neoadjuvant therapy in advanced breast cancer by baseline B-mode ultrasound, shear-wave elastography, and pathological information

Background Neoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer. Methods This retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models. Results All patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05). Conclusion As the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer.
Bacterial pathogens in pediatric appendicitis: a comprehensive retrospective study

Background Appendicitis is a frequent condition, with peak incidences in the second decade of life. Its pathogenesis is under debate, but bacterial infections are crucial, and antibiotic treatment remains essential. Rare bacteria are accused of causing complications, and various calculated antibiotics are propagated, yet there is no comprehensive microbiological analysis of pediatric appendicitis. Here we review different pre-analytic pathways, identify rare and common bacterial pathogens and their antibiotic resistances, correlate clinical courses, and evaluate standard calculated antibiotics in a large pediatric cohort. Method We reviewed 579 patient records and microbiological results of intraoperative swabs in standard Amies agar media or fluid samples after appendectomies for appendicitis between May 2011 and April 2019. Bacteria were cultured and identified via VITEK 2 or MALDI-TOF MS. Minimal inhibitory concentrations were reevaluated according to EUCAST 2022. Results were correlated to clinical courses. Results Of 579 analyzed patients, in 372 patients we got 1330 bacterial growths with resistograms. 1259 times, bacteria could be identified to species level. 102 different bacteria could be cultivated. 49% of catarrhal and 52% of phlegmonous appendices resulted in bacterial growth. In gangrenous appendicitis, only 38% remained sterile, while this number reduced to 4% after perforation. Many fluid samples remained sterile even when unsterile swabs had been taken simultaneously. 40 common enteral genera were responsible for 76.5% of bacterial identifications in 96.8% of patients. However, 69 rare bacteria were found in 187 patients without specifically elevated risk for complications. Conclusion Amies agar gel swabs performed superior to fluid samples and should be a standard in appendectomies. Even catarrhal appendices were only sterile in 51%, which is interesting in view of a possible viral cause. According to our resistograms, the best in vitro antibiotic was imipenem with 88.4% susceptible strains, followed by piperacillin-tazobactam, cefuroxime with metronidazole, and ampicillin-sulbactam to which only 21.6% of bacteria were susceptible. Bacterial growths and higher resistances correlate to an elevated risk of complications. Rare bacteria are found in many patients, but there is no specific consequence regarding antibiotic susceptibility, clinical course, or complications. Prospective, comprehensive studies are needed to further elicit pediatric appendicitis microbiology and antibiotic treatment.
Genomic prediction with haplotype blocks in wheat

Haplotype blocks might carry additional information compared to single SNPs and have therefore been suggested for use as independent variables in genomic prediction. Studies in different species resulted in more accurate predictions than with single SNPs in some traits but not in others. In addition, it remains unclear how the blocks should be built to obtain the greatest prediction accuracies. Our objective was to compare the results of genomic prediction with different types of haplotype blocks to prediction with single SNPs in 11 traits in winter wheat. We built haplotype blocks from marker data from 361 winter wheat lines based on linkage disequilibrium, fixed SNP numbers, fixed lengths in cM and with the R package HaploBlocker. We used these blocks together with data from single-year field trials in a cross-validation study for predictions with RR-BLUP, an alternative method (RMLA) that allows for heterogeneous marker variances, and GBLUP performed with the software GVCHAP. The greatest prediction accuracies for resistance scores for B. graminis, P. triticina, and F. graminearum were obtained with LD-based haplotype blocks while blocks with fixed marker numbers and fixed lengths in cM resulted in the greatest prediction accuracies for plant height. Prediction accuracies of haplotype blocks built with HaploBlocker were greater than those of the other methods for protein concentration and resistances scores for S. tritici, B. graminis, and P. striiformis. We hypothesize that the trait-dependence is caused by properties of the haplotype blocks that have overlapping and contrasting effects on the prediction accuracy. While they might be able to capture local epistatic effects and to detect ancestral relationships better than single SNPs, prediction accuracy might be reduced by unfavorable characteristics of the design matrices in the models that are due to their multi-allelic nature.
Identification and experimental validation of mitochondria-related genes biomarkers associated with immune infiltration for sepsis

Background Sepsis remains a complex condition with incomplete understanding of its pathogenesis. Further research is needed to identify prognostic factors, risk stratification tools, and effective diagnostic and therapeutic targets. Methods Three GEO datasets (GSE54514, GSE65682, and GSE95233) were used to explore the potential role of mitochondria-related genes (MiRGs) in sepsis. WGCNA and two machine learning algorithms (RF and LASSO) were used to identify the feature of MiRGs. Consensus clustering was subsequently carried out to determine the molecular subtypes for sepsis. CIBERSORT algorithm was conducted to assess the immune cell infiltration of samples. A nomogram was also established to evaluate the diagnostic ability of feature biomarkers via “rms” package. Results Three different expressed MiRGs (DE-MiRGs) were identified as sepsis biomarkers. A significant difference in the immune microenvironment landscape was observed between healthy controls and sepsis patients. Among the DE-MiRGs, NDUFB3 was selected to be a potential therapeutic target and its significant elevated expression level was confirmed in sepsis using in vitro experiments and confocal microscopy, indicating its significant contribution to the mitochondrial quality imbalance in the LPS-simulated sepsis model. Conclusion By digging the role of these pivotal genes in immune cell infiltration, we gained a better understanding of the molecular immune mechanism in sepsis and identified potential intervention and treatment strategies.
A numerical study of the hemodynamic behavior and gas transport in cardiovascular systems with severe cardiac or cardiopulmonary failure supported by venoarterial extracorporeal membrane oxygenation

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) has been extensively demonstrated as an effective means of bridge-to-destination in the treatment of patients with severe ventricular failure or cardiopulmonary failure. However, appropriate selection of candidates and management of patients during Extracorporeal membrane oxygenation (ECMO) support remain challenging in clinical practice, due partly to insufficient understanding of the complex influences of extracorporeal membrane oxygenation support on the native cardiovascular system. In addition, questions remain as to how central and peripheral venoarterial extracorporeal membrane oxygenation modalities differ with respect to their hemodynamic impact and effectiveness of compensatory oxygen supply to end-organs. In this work, we developed a computational model to quantitatively address the hemodynamic interaction between the extracorporeal membrane oxygenation and cardiovascular systems and associated gas transport. Model-based numerical simulations were performed for cardiovascular systems with severe cardiac or cardiopulmonary failure and supported by central or peripheral venoarterial extracorporeal membrane oxygenation. Obtained results revealed that: 1) central and peripheral venoarterial extracorporeal membrane oxygenation modalities had a comparable capacity for elevating arterial blood pressure and delivering oxygenated blood to important organs/tissues, but induced differential changes of blood flow waveforms in some arteries; 2) increasing the rotation speed of extracorporeal membrane oxygenation pump (ω) could effectively improve arterial blood oxygenation, with the efficiency being especially high when ω was low and cardiopulmonary failure was severe; 3) blood oxygen indices (i.e., oxygen saturation and partial pressure) monitored at the right radial artery could be taken as surrogates for diagnosing potential hypoxemia in other arteries irrespective of the modality of extracorporeal membrane oxygenation; and 4) Left ventricular (LV) overloading could occur when ω was high, but the threshold of ω for inducing clinically significant left ventricular overloading depended strongly on the residual cardiac function. In summary, the study demonstrated the differential hemodynamic influences while comparable oxygen delivery performance of the central and peripheral venoarterial extracorporeal membrane oxygenation modalities in the management of patients with severe cardiac or cardiopulmonary failure and elucidated how the status of arterial blood oxygenation and severity of left ventricular overloading change in response to variations in ω. These model-based findings may serve as theoretical references for guiding the application of venoarterial extracorporeal membrane oxygenation or interpreting in vivo measurements in clinical practice.
Genome-wide association study for carcass weight in pasture-finished beef cattle in Hawai’i

Introduction: Genome-wide association studies (GWAS) have identified genetic markers for cattle production and reproduction traits. Several publications have reported Single Nucleotide Polymorphisms (SNPs) for carcass-related traits in cattle, but these studies were rarely conducted in pasture-finished beef cattle. Hawai’i, however, has a diverse climate, and 100% of its beef cattle are pasture-fed. Methods: Blood samples were collected from 400 cattle raised in Hawai’i islands at the commercial harvest facility. Genomic DNA was isolated, and 352 high-quality samples were genotyped using the Neogen GGP Bovine 100 K BeadChip. SNPs that did not meet the quality control standards were removed using PLINK 1.9, and 85 k high-quality SNPs from 351 cattle were used for association mapping with carcass weight using GAPIT (Version 3.0) in R 4.2. Four models were used for the GWAS analysis: General Linear Model (GLM), the Mixed Linear Model (MLM), the Fixed and Random Model Circulating Probability Unification (FarmCPU), the Bayesian-Information and Linkage-Disequilibrium Iteratively Nested Keyway (BLINK). Results and Discussion: Our results indicated that the two multi-locus models, FarmCPU and BLINK, outperformed single-locus models, GLM and MLM, in beef herds in this study. Specifically, five significant SNPs were identified using FarmCPU, while BLINK and GLM each identified the other three. Also, three of these eleven SNPs (“BTA-40510-no-rs”, “BovineHD1400006853”, and “BovineHD2100020346”) were shared by multiple models. The significant SNPs were mapped to genes such as EIF5, RGS20, TCEA1, LYPLA1, and MRPL15, which were previously reported to be associated with carcass-related traits, growth, and feed intake in several tropical cattle breeds. This confirms that the genes identified in this study could be candidate genes for carcass weight in pasture-fed beef cattle and can be selected for further breeding programs to improve the carcass yield and productivity of pasture-finished beef cattle in Hawai’i and beyond.