Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Different Methionine Levels in Low Protein Diets on Production Performance, Reproductive System, Metabolism, and Gut Microbiota in Laying Hens

This study investigated the effects of different levels of methionine (Met) in a low protein diet on the production performance, reproductive system, metabolism, and gut microbial composition of laying hens to reveal the underlying molecular mechanism of Met in a low protein diet on the host metabolism and gut microbial composition and function of hens. A total of 360 healthy 38-week-old Peking Pink laying hens with similar body conditions and egg production (EP) were randomly divided into four groups with nine replicates per treatment and 10 hens per replicate. The hens in each treatment group were fed low protein diets containing different levels of Met (0.25, 0.31, 0.38, and 0.47%, respectively) for 12 weeks. Feed and water were provided ad libitum throughout the trial period. The results showed that, compared with the 0.25% Met group, the final body weight (FBW), average daily gain (ADG), EP, egg weight (EW), and average daily feed intake (ADFI) in the other groups were significantly increased and feed egg ratio (FER) was decreased. Meanwhile, the EW and yield of abdominal fat (AFY) in the 0.47% Met group were higher than those in other groups. The triglyceride (TG), estradiol (E2), total protein (TP), albumin (ALB), and immunoglobulin A (IgA) in the 0.38 and 0.47% Met groups were higher than those in other groups. In addition, 16S rRNA gene sequencing revealed that there was no difference in the Sobs index, ACE index, and Shannon index among all groups. However, it is worth noting that feeding low protein diets with Met changed the gut microbial composition (e.g., the supplementation of Met increased the level of Lactobacillus and decreased the proportion of Faecalibacterium). Also, our results showed that the changes in gut microbial composition induced by the diets with different levels of Met were closely related to the changes of key parameters: ADFI, EW, FBW, TG, EM, EP, ADG, FER, and uric acid (UA). Our results highlight the role of adding an appropriate amount of Met to the low protein diet in laying hens, which could improve the gut microbial composition, production performance, reproductive system, and nutrient metabolism of laying hens. In conclusion, this study suggested that when the Met level was 0.38%, the production performance of the laying hens was pretty good.
Combining Gaussian Processes and Neural Networks in Surrogate Modelling for Covariance Matrix Adaptation Evolution Strategy

: This paper focuses on surrogate models for Co-variance Matrix Adaptation Evolution Strategy (CMA-ES) in continuous black-box optimization. Surrogate modeling has proven to be able to decrease the number of evaluations of the objective function, which is an important requirement in some real-world applications where the evaluation can be costly or time-demanding. Surrogate models achieve this by providing an approximation instead of the evaluation of the true objective function. One of the state-of-the-art models for this task is the Gaussian process. We present an approach to combining Gaussian processes with artiﬁcial neural networks, which was previously successfully applied to other machine learning domains. The experimental part employs data recorded from previous CMA-ES runs, allowing us to assess different settings of surrogate models without running the whole CMA-ES algorithm. The data were collected using 24 noiseless benchmark functions of the platform for comparing continuous optimizers COCO in 5 different dimensions. Overall, we used data samples from over 2.8 million generations of CMA-ES runs. The results examine and statistically compare six covariance functions of Gaussian processes with the neural network extension. So far, the combined model did not show up to outperform the Gaussian process alone. Therefore, in conclusion, we discuss possible reasons for this and ideas for future research.
The Electron Transfer Path Between Cytochrome C and Single-walled Carbon Manotubes Based on Quantum Mechanics

By analyzing the shortest path between cytochrome c (Cytc) and single-walled carbon nanotubes (SWNTs), the study investigated electron transfer mechanism. By simplifying the snapshots model of SWNT(10, 10)-(Cytc) at 10 ns, the charge density of the simplified model was calculated by using quantum mechanics simulation and the charge density image was drawn. On the basis, the study discussed and verified the electron transfer mechanism and paths between Cytc and SWNTs at the optimal localization. The result revealed that the electrons were transferred to Cytc protein from the surfaces of SWNTs through Cys18.
Graph Networks with Physics-aware Knowledge Informed in Latent Space

While physics conveys knowledge of nature built from an interplay between observations and theory, it has been considered less important for modeling deep neural networks. Despite the usefulness of physical rules, it is particularly challenging to leverage the knowledge for sparse data since most physics equations are well deﬁned on the continuous and dense space. In addition, it is even harder to inform the equations into a model if the observations are not fully governed by the given physical knowledge. In this work, we present a novel architecture to incorporate physics or domain knowledge given as a form of partial differential equations (PDEs) on sparse observations by utilizing graph structure. Moreover, we leverage the representation power of deep learning by in-forming the knowledge in latent space. We demonstrate that climate prediction tasks are signiﬁcantly improved and validate the effectiveness and importance of the proposed model.
Ruling Sets in Random Order and Adversarial Streams

The goal of this paper is to understand the complexity of a key symmetry breaking problem, namely the ( α, β )-ruling set problem in the graph streaming model. Given a graph G = ( V, E ), an ( α, β )-ruling set is a subset I ⊆ V such that the distance between any two vertices in I is at least α and the distance between a vertex in V and the closest vertex in I is at most β . This is a fundamental problem in distributed computing where it finds applications as a useful subroutine for other problems such as maximal matching, distributed colouring, or shortest paths. Additionally, it is a generalization of MIS, which is a (2 , 1)-ruling set. Our main results are two algorithms for (2 , 2)-ruling sets: 1
Communication-Efficient BFT Using Small Trusted Hardware to Tolerate Minority Corruption

Agreement protocols for partially synchronous networks tolerate fewer than one-third Byzantine faults. If parties are equipped with trusted hardware that prevents equivocation, then fault tolerance can be improved to fewer than one-half Byzantine faults, but typically at the cost of increased communication complexity. In this work, we present results that use small trusted hardware without worsening communication complexity assuming the adversary controls a fraction of the network that is less than one-half. In particular, we show a version of HotStuff that retains linear communication complexity in each view, leveraging trusted hardware to tolerate a minority of corruptions. Our result uses expander graph techniques to achieve efficient communication in a manner that may be of independent interest
Optimal Error-Free Multi-Valued Byzantine Agreement

Byzantine agreement (BA) is a distributed consensus problem where n processors want to reach agreement on an ℓ -bit message or value, but up to t of the processors are dishonest or faulty. The challenge of this BA problem lies in achieving agreement despite the presence of dishonest processors who may arbitrarily deviate from the designed protocol. In this work by using coding theory, together with graph theory and linear algebra, we design a co ded BA protoc ol (termed as COOL) that achieves consensus on an ℓ -bit message with optimal resilience , asymptotically optimal round complexity , and asymptotically optimal communication complexity when ℓ ≥ t log t , simultaneously. The proposed COOL is a deterministic BA protocol that is guaranteed to be correct in all executions ( error free ) and does not rely on cryptographic technique such as signatures, hashing, authentication and secret sharing ( signature free ). It is secure against computationally unbounded adversary who takes full control over the dishonest processors ( information-theoretic secure ). The main idea of the proposed COOL is to use a carefully-crafted error correction code that provides an efficient way of exchanging “compressed” information among distributed nodes, while keeping the ability of detecting errors, masking errors, and making a consistent and validated agreement at honest distributed nodes. We show that our results can also be extended to the setting of Byzantine broadcast, aka Byzantine generals problem, where the honest processors want to agree on the message sent by a leader who is potentially dishonest. The results reveal that coding is an effective approach for achieving the fundamental limits of Byzantine agreement and its variants. Our protocol analysis borrows tools from coding theory, graph theory and linear algebra.
Kirigami-patterned highly stretchable conductors from flexible carbon nanotube-embedded polymer films

Achieving stretchable conductors with high stretchability and stable conductivity is a great challenge but urgent for multifunctional electronics applications. A novel kirigami-patterned stretchable conductive film (KSCF) with a highly tunable structure is prepared by laser cutting composites of carbon nanotube (CNT) conductive networks and an elastic poly(dimethylsiloxane) (PDMS) substrate. The kirigami film with an optimal structure exhibits both superior ultimate elongation as high as 430% and stable conductivity under high strain levels even up to 380%. More impressively, it also possesses excellent reversibility from 0 to 400% strain after 5000 repeated stretching cycles with negligible hysteresis and unchanged conductivity. The stress finite element modelling results further demonstrate that the effective stress-absorption through structural transformation is able to greatly enhance the KSCF stretchability and dynamic electrical stability. The as-prepared highly stretchable films present huge potential for emerging applications in stretchable electronics, especially those operating at high strain levels.
Neuroadrenergic activation in obstructive sleep apnea syndrome: a systematic review and meta-analysis

Supplemental Digital Content is available in the text Background: Neuroadrenergic overdrive occurs in obstructive sleep apnea syndrome (OSAS). However, the small sample size of the microneurographic studies, heterogeneity of the patients examined, presence of comorbidities, represented major weaknesses not allowing to precisely define the main features of the phenomenon, particularly in nonobese patients. Objective: This meta-analysis evaluated 850 participants recruited in 26 microneurographic studies, based on muscle sympathetic nerve activity (MSNA) quantification in uncomplicated OSAS of different clinical severity. Methods: The evaluation was extended to the relationships of MSNA with heart rate (HR), anthropometric and blood pressure (BP) values, metabolic variables, apnea–hypopnea index (AHI) and oxygen saturation. Results: MSNA is activated markedly and almost homogeneously between studies, showing a progressive increase from the healthy state to mild, moderate and severe OSAS (41.6, 48.3, 65.5 and 70.7 bursts/100 heart beats, respectively, P < 0.01). Of special interest are the findings that first, MSNA is significantly related to the AHI, a marker of OSAS severity (r = 0.55, P < 0.02) and O2 saturation but not to body weight and BMI, as it occurs in OSAS associated with obesity; and second, HR is significantly and directly related to MSNA and AHI (r = 0.56 and 0.46, P < 0.03 for both), thus representing a surrogate marker of the sympathetic overdrive. Conclusion: OSAS, even when uncomplicated by other cardiometabolic disease, displays a marked sympathetic activation, reflected by the MSNA and HR behavior, becoming a target of therapeutic interventions aimed at exerting sympathomoderating effects, such as continuous positive airway pressure.
The impact of venous resection in pancreatoduodectomy

Supplemental Digital Content is available in the text Abstract Background: Vein resection pancreatoduodenectomy (VRPD) may be performed in selected pancreatic cancer patients. However, the main risks and benefits related to VRPD remain controversial. Objective: This review aimed to evaluate the risks and survival benefits that the VRPD may add when compared with standard pancreatoduodenectomy (PD). Methods: A systematic review and meta-analysis of studies comparing VRPD and PD were performed. Results: VRPD was associated with a higher risk for postoperative mortality (risk difference: −0.01; 95% confidence interval [CI] −0.02 to −0.00) and complications (risk difference: −0.05; 95% CI −0.09 to −0.01) than PD. The length of hospital stay was not different between the groups (mean difference [MD]: −0.65; 95% CI −2.11 to 0.81). In the VRPD, the operating time was 69 minutes higher on average (MD: −69.09; 95% CI −88.4 to −49.78), with a higher blood loss rate (MD: −314.04; 95% CI −423.86 to −195.22). In the overall survival evaluation, the hazard ratio for mortality during follow-up on the group of VRPD was higher compared to the PD group (hazard ratio: 1.13; 95% CI 1.03–1.23). Conclusion: VRPD is associated with a higher risk of short-term complications and mortality and a lower probability of survival than PD. Knowing the risks and potential benefits of surgery can help clinicians to properly manage pancreatic cancer patients with venous invasion. The decision for surgery with major venous resection should be shared with the patients after they are informed of the risks and prognosis.
Prevalence and factors associated with HIV-1 drug resistance mutations in treatment-experienced patients in Nairobi, Kenya

Abstract An estimated 1.5 million Kenyans are HIV-seropositive, with 1.1 million on antiretroviral therapy (ART), with the majority of them unaware of their drug resistance status. In this study, we assessed the prevalence of drug resistance to nucleoside reverse transcriptase inhibitors (NRTIs), nucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors, and the variables associated with drug resistance in patients failing treatment in Nairobi, Kenya. This cross-sectional study utilized 128 HIV-positive plasma samples obtained from patients enrolled for routine viral monitoring in Nairobi clinics between 2015 and 2017. The primary outcome was human immunodeficiency virus type 1 (HIV-1) drug resistance mutation counts determined by Sanger sequencing of the polymerase (pol) gene followed by interpretation using Stanford's HIV Drug Resistance Database. Poisson regression was used to determine the effects of sex, viral load, age, HIV-subtype, treatment duration, and ART-regimen on the primary outcome. HIV-1 drug resistance mutations were found in 82.3% of the subjects, with 15.3% of subjects having triple-class ART resistance and 45.2% having dual-class resistance. NRTI primary mutations M184 V/I and K65R/E/N were found in 28.8% and 8.9% of subjects respectively, while NNRTI primary mutations K103N/S, G190A, and Y181C were found in 21.0%, 14.6%, and 10.9% of subjects. We found statistically significant evidence (P = .013) that the association between treatment duration and drug resistance mutations differed by sex. An increase of one natural-log transformed viral load unit was associated with 11% increase in drug resistance mutation counts (incidence rate ratio [IRR] 1.11; 95% CI 1.06–1.16; P < .001) after adjusting for age, HIV-1 subtype, and the sex-treatment duration interaction. Subjects who had been on treatment for 31 to 60 months had 63% higher resistance mutation counts (IRR 1.63; 95% CI 1.12–2.43; P = .013) compared to the reference group (<30 months). Similarly, patients on ART for 61 to 90 months were associated with 133% higher mutation counts than the reference group (IRR 2.33; 95% CI 1.59–3.49; P < .001). HIV-1 subtype, age, or ART-regimen were not associated with resistance mutation counts. Drug resistance mutations were found in alarmingly high numbers, and they were associated with viral load and treatment time. This finding emphasizes the importance of targeted resistance monitoring as a tool for addressing the problem.
Celiac disease: clinical update

Purpose of review This review highlights literature from the past year and explores the impact on current understanding of celiac disease pathogenesis, diagnosis, and management. Recent findings In contrast to earlier clinical trials, recent data suggests that early gluten introduction may protect against the development of celiac disease. Celiac disease is underdiagnosed, associated with high burden of disease and linked to excess mortality risk, yet, there remains considerable uncertainty regarding the utility of mass screening in asymptomatic individuals. The gut microbiome is increasingly implicated in celiac disease pathogenesis, although the exact mechanism is undefined. Probiotics have been proposed as a disease-modifying option for celiac disease but most studies assessing efficacy are of low-quality. Patients with celiac disease do not appear to be at increased risk of contracting or developing adverse outcomes from COVID-19. Little is known about the pathogenesis of nonceliac gluten sensitivity; however, recent findings suggest an autoimmune basis for the condition. Summary Current understanding of celiac disease continues to advance, though significant knowledge gaps remain. Large, rigorous, prospectively designed studies are needed to further characterize celiac disease pathogenesis, management and therapeutic options.
Bacteriological profile and antibiotics used for septic patients in Karbala, Iraq

Background: Sepsis is an issue of globular health care, characterized by complete inflammation of the body in response to microbial infection, which results in organ malfunction. This becomes a chronic patient complication. Therefore, sepsis may be a diverse and combined disease with varying etiology, severity, and treatment plan. Objectives: The purpose of this study was to demonstrate the existence of exposure and the resistance of microorganisms to the range of antibiotics in subjects of the local community. Results: Among 11 species of bacteria isolated from a variety of specimens, Escherichia coli (22.1%) and Staphylococcus aureus (20.3%) were the most common organism found over the subjects had been collected. The most sensitive antibiotics for Gram-negative E. coli were colistin 97%, imipenem 89%, meropenem 88%, and amikacin 79%, while the highest resistant rate was benzylpenicillin 93%, and oxacillin 86%. Methicillin-resistant S. aureus (MRSA) prevalence was 90%, vancomycin-resistant S. aureus (VRSA) 31%. Conclusion: Because of the high incidence of VRSA and MRSA, clinicians should become more vigilant in using vancomycin and another important antibiotic. Moreover, maintain this useful drug to be used for a prolonged time with good efficacy.
Clinical predictive risk factors prolonged the duration of SARS-CoV-2 clearance in 279 moderate COVID-19 patients

Supplemental Digital Content is available in the text Abstract The results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid as one of the criteria has been widely applied to assess whether the coronavirus disease 2019 (COVID-19) patients could discharge, however, the risk factors that affect the duration of the SARS-CoV-2 clearance remained to be an enigma. Our research was to identify risk factors correlated with prolonged duration of the SARS-CoV-2 clearance in moderate COVID-19 patients. We retrospectively analyzed 279 consecutive ordinary COVID-19 patients in 3 hospitals in Hubei province including Huangshi Hospital of Infectious Disease, Wuhan Thunder God Mountain Hospital, and Tongji Hospital. Eight clinical characters were contained as risk factors. We used a logistic regression model and nomogram to assess the possibility that the SARS-CoV-2 nucleic acid may turn negative in 14 days. Time from symptoms onset to diagnosis (odds ratio [OR] = 3.18; 95% confidence interval [CI] 1.56–6.46; P = .001), time from onset use of antiviral drugs to onset of symptoms (OR = 0.41; 95% CI 0.23–0.72; P = .02), and bacterial coinfection (OR = 0.07; 95% CI 0.01–0.86; P = .038) were independent risks factors for the duration of SARS-CoV-2 nucleic acid clearance. The regression model showed good accuracy and sensitivity (area under the curve = 0.96). Nomogram was also provided to predict the negative conversion rate of SARS-CoV-2 nucleic acids within 14 days. Time from symptoms onset to diagnosi, time from onset use of antiviral drugs to onset of symptoms, and bacterial coinfection were independent risk factors for the time of SARS-CoV-2 nucleic acid turning negative in ordinary COVID-19 patients. However, the age, gender, underlying disease, fungal coinfection, and duration use of antiviral drugs were irrelevant factors.
The efficacy and safety of glucokinase activators for the treatment of type-2 diabetes mellitus

Abstract Background: Glucokinase activators (GKAs) are a novel family of glucose-lowering agents used for the treatment of type-2 diabetes mellitus. Treatment with different GKAs has been shown to reduce blood glucose levels in these patients. We compared the efficacy/safety of GKAs in patients with type-2 diabetes mellitus through a meta-analysis. Methods: We searched the PubMed, Excerpt Medica Database, and Cochrane Central Register of Controlled Trials databases for articles published before December 30, 2020. We computed the weighted mean difference (WMD) and 95% confidence interval (CI) for the change from baseline to the study endpoint for GKA versus placebo treatments. Results: A total of 4 articles (5 studies) were included in the meta-analysis. GKAs were associated with reductions in glycated hemoglobin levels from baseline (WMD, −0.3%; 95% CI, −0.466% to −0.134%). No significant difference between GKA and placebo treatment was observed in the results of fasting plasma glucose levels from baseline (WMD 0.013 mmol/L; 95% CI, −0.304–0.33 mmol/L). A significantly higher change in 2-hour postprandial plasma glucose (2-h PPG) levels (WMD −2.434 mmol/L; 95% CI, −3.304 to −1.564 mmol/L) was observed following GKA than placebo treatment. GKAs were associated with a higher prevalence of causing hypoglycemic events than placebo treatment (risk difference [RD], 0.06; 95% CI 0.013–0.106). GKAs had no association with the risk of developing adverse effects (RD, 0.038; 95% CI, −0.03–0.106) and serious adverse events (RD, 0.01; 95% CI, −0.004–0.023). Conclusions: GKAs were more effective for postprandial blood glucose control. However, these agents showed a significantly high risk of causing hypoglycemia. PROSPERO registration number: CRD42021220364.