Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in the microbiome of the small intestine of Leghorn lines divergently selected for antibody titer to sheep erythrocytes suggest roles for commensals in host humoral response

For forty generations, two lines of White Leghorn chickens have been selected for high (HAS) or low (LAS) antibody response to a low dose injection of sheep red blood cells (SRBCs). Their gut is home to billons of microorganisms and the largest number of immune cells in the body; therefore, the objective of this experiment was to gain understanding of the ways the microbiome may influence the differential antibody response observed in these lines. We achieved this by characterizing the small intestinal microbiome of HAS and LAS chickens, determining their functional microbiome profiles, and by using machine learning to identify microbes which best differentiate HAS from LAS and associating the abundance of those microbes with host gene expression. Microbiome sequencing revealed greater diversity in LAS but statistically higher abundance of several strains, particularly those of Lactobacillus, in HAS. Enrichment of microbial metabolites implicated in immune response such as lactic acid, short chain fatty acids, amino acids, and vitamins were different between HAS and LAS. The abundance of several microbial strains corresponds to enriched host gene expression pathways related to immune response. These data provide a compelling argument that the microbiome is both likely affected by host divergent genetic selection and that it exerts influence on host antibody response by various mechanisms.
Time-Sensitive Federated Learning With Heterogeneous Training Intensity: A Deep Reinforcement Learning Approach

Federated learning (FL) has recently received sufficient attention because of its capability of collaboratively training machine learning models without exposing data privacy. Most existing FL schemes assume the fixed or predetermined local training intensities/iterations at clients for each communication round, which however neglects the effect of local training intensity determination on the performance of FL. Besides that, in traditional FL, the clients are assigned to conduct the same number of training iterations. In this context, the client with low computation or communication capability may slow down the global model aggregation, which causes high waiting latency at other clients. To address these issues, this paper proposes a novel Time-sensitive FL mechanism with Heterogeneous Training Intensity at clients, named TFL_HTI. Specifically, we first explore the bounded convergence rate of FL with heterogeneous training iterations. Then, we design a Deep Reinforcement Learning (DRL) approach to determine the overall training intensity of clients in each communication round. Based on this, we further design an optimal deterministic algorithm to assign the appropriate local iterations to clients based on their training capabilities. Finally, we conduct simulations to demonstrate the effectiveness of our proposed scheme.
Identification of mitophagy-related biomarkers in human osteoporosis based on a machine learning model

Background: Osteoporosis (OP) is a chronic bone metabolic disease and a serious global public health problem. Several studies have shown that mitophagy plays an important role in bone metabolism disorders; however, its role in osteoporosis remains unclear. Methods: The Gene Expression Omnibus (GEO) database was used to download GSE56815, a dataset containing low and high BMD, and differentially expressed genes (DEGs) were analyzed. Mitochondrial autophagy-related genes (MRG) were downloaded from the existing literature, and highly correlated MRG were screened by bioinformatics methods. The results from both were taken as differentially expressed (DE)-MRG, and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Protein-protein interaction network (PPI) analysis, support vector machine recursive feature elimination (SVM-RFE), and Boruta method were used to identify DE-MRG. A receiver operating characteristic curve (ROC) was drawn, a nomogram model was constructed to determine its diagnostic value, and a variety of bioinformatics methods were used to verify the relationship between these related genes and OP, including GO and KEGG analysis, IP pathway analysis, and single-sample Gene Set Enrichment Analysis (ssGSEA). In addition, a hub gene-related network was constructed and potential drugs for the treatment of OP were predicted. Finally, the specific genes were verified by real-time quantitative polymerase chain reaction (RT-qPCR). Results: In total, 548 DEGs were identified in the GSE56815 dataset. The weighted gene co-expression network analysis(WGCNA) identified 2291 key module genes, and 91 DE-MRG were obtained by combining the two. The PPI network revealed that the target gene for AKT1 interacted with most proteins. Three MRG (NELFB, SFSWAP, and MAP3K3) were identified as hub genes, with areas under the curve (AUC) 0.75, 0.71, and 0.70, respectively. The nomogram model has high diagnostic value. GO and KEGG analysis showed that ribosome pathway and cellular ribosome pathway may be the pathways regulating the progression of OP. IPA showed that MAP3K3 was associated with six pathways, including GNRH Signaling. The ssGSEA indicated that NELFB was highly correlated with iDCs (cor = −0.390, p < 0.001). The regulatory network showed a complex relationship between miRNA, transcription factor(TF) and hub genes. In addition, 4 drugs such as vinclozolin were predicted to be potential therapeutic drugs for OP. In RT-qPCR verification, the hub gene NELFB was consistent with the results of bioinformatics analysis. Conclusion: Mitophagy plays an important role in the development of osteoporosis. The identification of three mitophagy-related genes may contribute to the early diagnosis, mechanism research and treatment of OP.
FREQUENCY OF CAUSES OF PANCYTOPENIA IN BONE MARROW SAMPLES OF PATIENTS

Objective: The aim of this study is to find out the common causes that lead to pancytopenia in our population specially in the province of Punjab. Material and Methods: This is a cross sectional study that was conducted at Chughtai Institute of Pathology, Lahore. The duration of the study was from June 2020 to December 2021. A total of 210 patients were included in the study. A through history was taken and complete physical examination was done prior to the bone marrow biopsy procedure. Peripheral blood sample was run on Sysmex XN 9000 automated hematology analyzer. Bone marrow aspirate and trephine biopsy were thoroughly examined and immunohistochemical stains were applied where required. The data was analyzed using SPSS 23.0 and frequencies were calculated. Results: Most common causes of pancytopenia in our study were megaloblastic anemia (18.1%) followed by aplastic anemia (12.9%), immune mediated causes (12.4%), acute myeloid leukemia (11%), hypocellular marrow (9%) myelodysplastic syndrome (6.2%), hypersplenism (5.2%) and Precursor B acute lymphoblastic leukemia (5.2%) (Fig. 2). Other causes include B cell non-Hodgkin lymphoma (4.8%), mixed deficiency anemia (4.2%), hypersplenism (3.8%), Gaucher’s disease (1.4%), infections (1%) and other miscellaneous causes (4.8%). Conclusion: The study conducted at our institute showed that majority of patients had benign causes (69.2%) leading to pancytopenia, the most common cause being megaloblastic anemia. Malignant causes constitute only a minority of cases of pancytopenia. Key Words: Bone marrow biopsy, Frequency, Pancytopenia
Local variability in growth and reproduction of Salix arctica in the High Arctic

Arctic terrestrial ecosystems are heterogeneous because of the strong influences of microtopography, soil moisture and snow accumulation on vegetation distribution. The interaction between local biotic and abiotic factors and global climate patterns will influence species responses to climate change. Salix arctica (Arctic willow) is a structuring species, ubiquitous and widespread, and as such is one of the most important shrub species in the High Arctic. In this study, we measured S. arctica reproductive effort, early establishment, survival and growth in the Zackenberg valley, north-east Greenland. We sampled four plant communities that varied with respect to snow conditions, soil moisture, nutrient content and plant composition. We found large variability in reproductive effort and success with total catkin density ranging from 0.6 to 66 catkins/m2 and seedling density from <1 to 101 seedlings/m2. There were also major differences in crown area increment (4–23 cm2/year) and stem radial growth (40–74 µm/year). The snowbed community, which experienced a recent reduction in snow cover, supported young populations with high reproductive effort, establishment and growth. Soil nutrient content and herbivore activity apparently did not strongly constrain plant reproduction and growth, but competition by Cassiope tetragona and low soil moisture may inhibit performance. Our results show that local environmental factors, such as snow accumulation, have a significant impact on tundra plant response to climate change and will affect the understanding of regional vegetation response to climate change.
Clinical implementation of three-dimensional standardized template-guided brachytherapy for patients with locally advanced cervical cancer

Purpose Although customized three-dimensional (3D) templates have shown advantages in brachytherapy, widespread application is still full of challenges. The present work proposed the use of a commercial 3D standardized template-guided intracavitary/interstitial brachytherapy (IC/ISBT) that could provide simple and reproducible needles’ insertion. Material and methods 43 patients received external beam radiotherapy (EBRT) with 45-50.4 Gy and subsequent IC/ISBT with 28 Gy in 4 fractions. In terms of IC/ISBT, 24 patients were treated with 3D standardized templates (ST group), and 19 patients were treated using free-hand implantation (FH group). Consistency of implantation for all needles and dosimetric differences for target and organs at risk (OARs) were then compared between two groups. Results The mean variation of tip position between insertions for needles was 1.41 mm and 2.74 mm in ST group and FH group, respectively (p < 0.001). ST group was superior in terms of dosimetric conformity index (CI) and D90 for high-risk clinical target volume (HR-CTV), significantly improving to 23.21% (p < 0.001) and 3.58% (p = 0.031) compared with FH group. The D2cc of the bladder and sigmoid in the ST group were lower than those in the FH group (p < 0.05). Meanwhile, a strong correlation between the volume of HR-CTV and its CI in the ST group (R = 0.865, p < 0.001) was found with Spearman’s correlation analysis. Conclusions The implementation of 3D standardized template can potentially improve the precision and consistency in the needle insertion procedure that may replace some customized 3D templates, and achieve clinical satisfied dose distribution in IC/ISBT plans for patients with LACC.
The saccadic training for driving safety

Abstract Driving is not only a physical but also a mental task. Human errors such as misperception, information processing errors, and poor decision making are frequently identified as causes of accidents. Objective: to reduce numbers of saccadic movements (SM) and antisaccadic movements (ASM) while driving because they involve a problem of visual perception. During each one of them, the visual scene sweeps across the retina with high-speed motion with an inevitable blurring of the image, as the retina is sweeping the visual field. Object positions in retinal coordinates change, the entire visual image is not updated and humans become effectively blind but usually we are not aware of this blur during the eye movement. Therefore, reducing the number of SM allows greater precision in visual information and thus increases safety. Study Design: in collaboration with the Directorate of Specialties of the State Police of Italian Ministry of the Interior and the Autodrome of Modena we have submitted to saccadic training 23 policemen of Italian traffic police. We used Visual Exploration Training System (VET by SVEP®) which consists in: personal computer, eyetracking system (120 Hz of frequency analisys) and new specific application software. Subjects were evaluated before and after 15 days of home training. Results: In the overall 23 cases the training significantly reduced the number of SM in driving simulation. Conclusions: our fast and easy-to-use method of saccadic training seems to be able to improve significantly both the function of visual exploration and the safety in driving. Abbreviations ADI: Number of saccades not directed towards the target point or rather attention deficit index; ASMs: anti-saccadic movements; AT: attentional test: the subject had to maintain fixation on a target point that appeared randomly on the monitor in 50 different positions in 50 s even during the recurrent appearance of new distracting images; CORSI: score of eCorsi Span Test; GROUP A and GROUP B: groups of policemen; ORD: ordinary road drivers; RD: racing drivers; RT: average start time of ocular movements; ST: saccade test: the subject had to fix a target point that appeared randomly on the monitor in 31 different positions in 23 s; SM: saccadic movements; ST: saccade test; TIME: the time on the lap during real driving; TRT: target reaching time; VET: visual exploration training system; VETT 1: visual exploration test for evaluate SM and ASM; VETT 2: visual exploration test for evaluate the number of SM during simulated driving
Freshwater biodiversity crisis: macroinvertebrates response to receiving a wastewater treatment plant effluent along a downstream gradient

Suburban watercourses receiving sewage effluents often are low-flow and not modified, unlike large rivers to which wastewater is discharged. The impact of chemical pollutants on biodiversity as well as the effectiveness of ecosystem recovery and self-purification are worth careful attention. The aim was to assess the macroinvertebrates’ responses to receiving an input from a wastewater treatment plant (WWTP) along the downstream gradient. We studied the variability and recovery pattern of macroinvertebrates in six sections located along a sewage receiving stream continuum. The comparison of chemical parameters showed significant differences in the pH, BOD 5 , N-NH 4 + and PO 4 3. At sites 100, 300 and 500 m downstream of the WWTP, the persistently high amount of pathogenic coliform bacteria testified to the high impact of bacteriological pollution of sewage on the receiver. Based on 18013 macroinvertebrates, non-metric multidimensional scaling showed differences between the assemblages at the sections upstream of the WWTP, and located downstream. Effluent discharge affected the macroinverte-brate, causing a decrease of its quantitative index (abundance) by 7% and qualitative index (EPT) by 26% at the site of the sewage discharge. The recovery pattern was manifested by the gradual increase in macoinvertebrate indices at the sites located downstream from the WWTP, which at distances of 300 m and 500 m from the discharge site attained comparable values to those at the reference sites upstream of the WWTP. The populations of the most sensitive taxa were not fully restored with increasing distance from the WWTP, even at a distance of 500 meters, but instead were replaced by more resistant taxa. More attention should be paid to the impact of wastewater discharge from suburban wastewater treatment plants on receiving watercourse biodiversity and ecological water conditions, especially in the case of small and low-flow sewage receivers, where self-purification processes are difficult.
Fault Diagnosis of Ship Ballast Water System Based on Support Vector Machine Optimized by Improved Sparrow Search Algorithm

The key to reducing operation and maintenance costs and improving reliability is to evaluate the condition and fault detection methods of ship ballast water systems. To reduce the impact of support vector machine (SVM) parameter uncertainty and improve the accuracy of ship ballast water system fault diagnosis models, this paper proposes a multi-strategy collaborative improved sparrow search algorithm (ISSA) to optimize the parameters of SVM for fault diagnosis. First, ISSA initializes the population using tent chaotic maps to improve spatial distribution uniformity and stabilize the population quality. Second, the discoverer in the algorithm adopts an adaptive weighting strategy to avoid falling into local optima and accelerate the convergence speed. Finally, the follower position introduces mutation strategies and chaotic perturbations to enhance local evolution capabilities and improve the utilization of search areas. The experimental results show that compared with sparrow search algorithm (SSA), particle swarm optimization algorithm (PSO), genetic Algorithm (GA), whale optimization algorithm (WOA), and grey wolf optimization algorithm (GWO), ISSA can obtain better optimal solutions at the fastest convergence rate on the benchmark test function. On the dataset of the ship ballast water system, the ISSA-SVM fault diagnosis model proposed in this paper has the best classification performance, with an average accuracy of 97.44%. Compared with the other two models, ISSA-SVM is 7.55% and 0.83% higher than SVM’s 89.89% and SSA-SVM’s 96.61%.
The impact of employees’ experience of high-performance work systems on innovative behavior in professional service firms

This research examines the impact of employees’ experience of high-performance work systems (HPWS) on their innovative behavior. The study draws upon social exchange theory to propose that employees’ experience of HPWS influences their innovative behavior directly and through sequential mediation of social capital development and knowledge-sharing behavior. Additionally, the study uses the Elaboration Likelihood Model to highlight that individuals’ need for cognition strengthens the relationship between employees’ knowledge-sharing and innovative behaviors. The study employed a time-lagged quantitative research design with survey data from 262 job incumbents in professional service firms. The proposed model was tested using the PLS-SEM two-stage approach. The findings of the study confirm the proposed direct and indirect relationships. Moreover, the findings also confirm that the need for cognition strengthens the relationship between knowledge-sharing and individual innovation behaviors. The study posits that employees’ experience of HRM systems can influence their innovative behavior as a reciprocal exchange toward the employer. Moreover, this study presents a comprehensive model that highlights the interplay of social and cognitive factors that can influence the relationship between HPWS and employees’ innovation behavior. This study also fills a gap in the existing literature by highlighting the antecedents of innovative behavior in professional service firms.
Postnatal foot length in the estimation of gestational age in relation to intrauterine growth pattern among Nigerian neonates

Objectives: To determine the relationship between postnatal foot lengths and estimated gestational age (EGA) in relation to intrauterine growth patterns determined at birth among Nigerian neonates.Design: Hospital-based, cross-sectional.Setting: Olabisi Onabanjo University Teaching Hospital, Sagamu, Nigeria.Participants: 260 neonates with EGA 30- 42 weeks within 48 hours of life.Interventions: Postnatal foot lengths (FL) were measured with Vernier digital calliper in millimetres. The intra-uterine growth pattern was determined using the Lubchenco chart. Pearson correlation and regression analysis tests were performed.Main outcome measures: Postnatal foot length in relation to Intra-Uterine Growth PatternResults: The mean postnatal FL had a strong positive correlation with the EGA from 30 through 42 weeks (r = 0.855, p < 0.001). The overall mean foot length for preterm neonates was 65.44 (6.92) mm, while that of term neonates was 77.92 (4.24) mm. The linear regression equation was generated as: EGA = 9.43 + (0.37 × FL), p < 0.001. The EGA as measured by FL had the highest positive correlation with Small for Gestational Age (SGA) intra-uterine-growth pattern, followed by Appropriate for Gestational Age (AGA) and least by Large for Gestational Age (LGA) respectively (r = 0.936> 0.861 > 0.666). Conclusion: The postnatal foot length correlated well with estimated gestational age, and the correlation was best among SGA infants.
The impact of Arctic sea ice change on midlatitude climate

Arctic sea ice loss is a robust feature of observations and of climate model projections. Amplified winter lower tropospheric warming in the Arctic relative to the global mean is associated with this ice loss. Many recent studies have addressed the possible effects of these changes on the midlatitude atmospheric circulation, particularly in the North Atlantic. These studies suggest responses including an equatorward jet shift, a negative annular mode response and changes in Rossby wave behaviour. However, there is disagreement on the magnitude, significance and even sign of these responses. Previous studies have shown the advantages of model hierarchies for understanding the atmosphere. In this thesis, experiments are conducted in HadGAM1 with simplified lower boundary conditions. Two sets of experiments are conducted, one in a zonally symmetric aquaplanet and the other in a configuration with representative northern hemisphere land masses. A wide range of sea ice profiles are imposed. The dominant response to ice removal in an aquaplanet is an equatorward jet shift, consistent with previous work. This response is moderate in magnitude for ice which does not exceed 65◦ latitude, but strongly nonlinear for greater ice extents. The zonal mean response is qualitatively similar in the asymmetric configuration, but the nature of the asymmetric response shows sensitivity to the exact ice edge location. These results have implications for understanding the impact of sea ice anomalies in past as well as present climates. Changes in surface temperature gradients, including from Arctic amplification, could affect midlatitude climate even if circulation changes are small. In particular, changes in thermal advection could alter midlatitude temperature variability and extremes. In this thesis a multiple regression model is used to investigate projected monthly temperature variance changes in a recent single model ensemble. Many robust changes, including reduced winter temperature variance in Europe, are consistent with the effect of changes in the seasonal mean temperature gradient alone.