Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic post-translational modification profiling of Mycobacterium tuberculosis-infected primary macrophages

Macrophages are highly plastic cells with critical roles in immunity, cancer, and tissue homeostasis, but how these distinct cellular fates are triggered by environmental cues is poorly understood. To uncover how primary murine macrophages respond to bacterial pathogens, we globally assessed changes in post-translational modifications of proteins during infection with Mycobacterium tuberculosis, a notorious intracellular pathogen. We identified hundreds of dynamically regulated phosphorylation and ubiquitylation sites, indicating that dramatic remodeling of multiple host pathways, both expected and unexpected, occurred during infection. Most of these cellular changes were not captured by mRNA profiling, and included activation of ubiquitin-mediated autophagy, an evolutionarily ancient cellular antimicrobial system. This analysis also revealed that a particular autophagy receptor, TAX1BP1, mediates clearance of ubiquitylated Mtb and targets bacteria to LC3-positive phagophores. These studies provide a new resource for understanding how macrophages shape their proteome to meet the challenge of infection.
Generalized Fitch Graphs III: Symmetrized Fitch maps and Sets of Symmetric Binary Relations that are explained by Unrooted Edge-labeled Trees

Binary relations derived from labeled rooted trees play an import role in mathematical biology as formal models of evolutionary relationships. The (symmetrized) Fitch relation formalizes xenology as the pairs of genes separated by at least one horizontal transfer event. As a natural generalization, we consider symmetrized Fitch maps, that is, symmetric maps $\varepsilon$ that assign a subset of colors to each pair of vertices in $X$ and that can be explained by a tree $T$ with edges that are labeled with subsets of colors in the sense that the color $m$ appears in $\varepsilon(x,y)$ if and only if $m$ appears in a label along the unique path between $x$ and $y$ in $T$. We first give an alternative characterization of the monochromatic case and then give a characterization of symmetrized Fitch maps in terms of compatibility of a certain set of quartets. We show that recognition of symmetrized Fitch maps is NP-complete. In the restricted case where $|\varepsilon(x,y)|\leq 1$ the problem becomes polynomial, since such maps coincide with class of monochromatic Fitch maps whose graph-representations form precisely the class of complete multi-partite graphs.
A new analogue of islet neogenesis associated protein with higher structural and plasma stability

Abstract Islet Neogenesis Associated Protein pentadecapeptide (INGAP-PP) increases β-cell mass and function in experimental animals. A short clinical trial also yielded promising results. However, HTD4010, a new peptide derived from INGAP-PP, was developed in order to optimize its specific effects by minimizing its side effects. To study and compare the tertiary structure, stability dynamics, and plasma stability of HTD4010, an INGAP-PP analogue. Both peptides were pre-incubated in human, rat and mouse plasma at 37 °C, and their presence was identified and quantified by high performance liquid chromatography at different time-points. GROMACS 2019 package and the Gromos 54A7 force field were used to evaluate overall correlated motion of the peptide molecule during molecular dynamics simulation by essential dynamics. HTD4010 exhibited significantly larger plasma stability than INGAP-PP, and its structural stability was almost 3.36-fold higher than INGAP-PP. These results suggest that HTD4010 may facilitate longer tissue interaction, thereby developing higher potential biological effects. If so, HTD4010 may become a promising therapeutic agent to treat people with diabetes. Communicated by Ramaswamy H. Sarma
Direct Visual-Inertial Ego-Motion Estimation Via Iterated Extended Kalman Filter

This letter proposes a reactive navigation strategy for recovering the altitude, translational velocity and orientation of Micro Aerial Vehicles. The main contribution lies in the direct and tight fusion of Inertial Measurement Unit (IMU) measurements with monocular feedback under an assumption of a single planar scene. An Iterated Extended Kalman Filter (IEKF) scheme is employed. The state prediction makes use of IMU readings while the state update relies directly on photometric feedback as measurements. Unlike feature-based methods, the photometric difference for the innovation term renders an inherent and robust data association process in a single step. The proposed approach is validated using real-world datasets. The results show that the proposed method offers better robustness, accuracy, and efficiency than a feature-based approach. Further investigation suggests that the accuracy of the flight velocity estimates from the proposed approach is comparable to those of two state-of-the-art Visual Inertial Systems (VINS) while the proposed framework is $\approx 15\text{--}30$ times faster thanks to the omission of reconstruction and mapping.
Underutilization of Pulmonary Function Testing in Veterans Hospitalized for Chronic Obstructive Pulmonary Disease Exacerbation: Who are We Missing?

Abstract Pulmonary function testing (PFT) is required to diagnose chronic obstructive pulmonary disease (COPD) but is completed for only 30-50% of patients with the disease. We determined patient factors associated with decreased likelihood for PFT acquisition (i.e. underutilization) in the United States Veterans Affairs (VA) health care system. We performed a retrospective analysis of Veterans who survived a VA-based COPD hospitalization between 2012 and 2015. COPD was identified using International Classification of Disease (ICD)-9 codes. Our primary outcome was PFT acquisition, using Current Procedural Terminology (CPT) codes any time prior to the index hospitalization. We compared patients with and without PFTs and used logistic regression to identify associations with PFT underutilization. Of the 48,888 Veterans included, 78% underwent PFTs prior to hospitalization. Patients without PFTs were younger and more likely to be: women (4.2% vs. 3.6%; p = 0.01), nonwhite (22% vs. 19%; p < 0.0001), and current smokers (66% vs 61%; p < 0.0001). PFT acquisition was less likely in Veterans with alcohol and drug use disorders. Using logistic regression, Veterans who were women (Odds Ratio (OR) = 1.17 [95% confidence limit 1.03–1.32]), nonwhite (OR 1.12 [1.06–1.20]), and with a history of alcohol (OR = 1.07 [1.00–1.14]) or drug use disorders (OR = 1.15 [1.06–1.24]) were less likely to undergo PFTs. Though most Veterans hospitalized for COPD had PFTs prior to admission, PFTs are underutilized in Veterans who are: women, younger, nonwhite, and have alcohol or drug use disorders. These groups may be “at-risk” for delayed diagnosis or substandard COPD quality care.
Approximate Kernel Selection via Matrix Approximation

Kernel selection is of fundamental importance for the generalization of kernel methods. This article proposes an approximate approach for kernel selection by exploiting the approximability of kernel selection and the computational virtue of kernel matrix approximation. We define approximate consistency to measure the approximability of the kernel selection problem. Based on the analysis of approximate consistency, we solve the theoretical problem of whether, under what conditions, and at what speed, the approximate criterion is close to the accurate one, establishing the foundations of approximate kernel selection. We introduce two selection criteria based on error estimation and prove the approximate consistency of the multilevel circulant matrix (MCM) approximation and Nyström approximation under these criteria. Under the theoretical guarantees of the approximate consistency, we design approximate algorithms for kernel selection, which exploits the computational advantages of the MCM and Nyström approximations to conduct kernel selection in a linear or quasi-linear complexity. We experimentally validate the theoretical results for the approximate consistency and evaluate the effectiveness of the proposed kernel selection algorithms.
Trends in mental health service utilization among LGB+ college students

Abstract Objectives 1) Compare service utilization among LGB+ and straight-identified students. 2) Assess rates of mental health concerns among LGB+ students only. Participants: Undergraduates (N = 675) reported on their sexual orientation, mental health conditions, and past service providers. Methods: Logistic regression was used for aim 1 and descriptive statistics for aim 2. Results: LGB+ students were more likely than straight-identified students to seek services for anxiety (odds ratio [OR] = 2.051; p < .01) or depression (OR = 3.058; p < .001) and from a counselor/therapist/psychologist (OR = 2.937; p < .001) or their university’s counseling/health services (OR = 1.933; p < .01). Bisexual students utilized the most services. Conclusions: Colleges must ensure that programing, outreach, and overall support for the mental health needs of their LGB+ students are being met so that this vulnerable population continues to seek services.
Identification of Differentially Expressed Proteins in Sugarcane in Response to Infection by Xanthomonas albilineans Using iTRAQ Quantitative Proteomics

Sugarcane can suffer severe yield losses when affected by leaf scald, a disease caused by Xanthomonas albilineans. This bacterial pathogen colonizes the vascular system of sugarcane, which can result in reduced plant growth and plant death. In order to better understand the molecular mechanisms involved in the resistance of sugarcane to leaf scald, a comparative proteomic study was performed with two sugarcane cultivars inoculated with X. albilineans: one resistant (LCP 85-384) and one susceptible (ROC20) to leaf scald. The iTRAQ (isobaric tags for relative and absolute quantification) approach at 0 and 48 h post-inoculation (hpi) was used to identify and annotate differentially expressed proteins (DEPs). A total of 4295 proteins were associated with 1099 gene ontology (GO) terms by GO analysis. Among those, 285 were DEPs during X. albilineans infection in cultivars LCP 85-384 and ROC20. One hundred seventy-two DEPs were identified in resistant cultivar LCP 85-384, and 113 of these proteins were upregulated and 59 were downregulated. One hundred ninety-two DEPs were found in susceptible cultivar ROC20 and half of these (92) were upregulated, whereas the other half corresponded to downregulated proteins. The significantly upregulated DEPs in LCP 85-384 were involved in metabolic pathways, the biosynthesis of secondary metabolites, and the phenylpropanoid biosynthesis pathway. Additionally, the expression of seven candidate genes related to photosynthesis and glycolytic pathways, plant innate immune system, glycosylation process, plant cytochrome P450, and non-specific lipid transfer protein was verified based on transcription levels in sugarcane during infection by X. albilineans. Our findings shed new light on the differential expression of proteins in sugarcane cultivars in response to infection by X. albilineans. The identification of these genes provides important information for sugarcane variety improvement programs using molecular breeding strategies.
Thermohaline Structures and Heat/Freshwater Transports of Mesoscale Eddies in the Bay of Bengal Observed by Argo and Satellite Data

Knowledge of mesoscale eddies in the Bay of Bengal (BOB) is key for further understanding the climate variability in this region and beyond, but little is known about the vertical structure of these eddies. In this study, the three−dimensional structure and transport characteristics of mesoscale eddies in the BOB were comprehensively investigated by the combined use of Argo profiles and satellite data. The composite analysis showed that eddy−induced ocean anomalies are mainly confined to the upper 300 m of the water. The spatial structure of eddy−induced thermohaline perturbations is characterized by a dominant dipole structure in the near surface layer, arising from horizontal advection of the background thermohaline gradient by eddy rotation, and a monopole structure in the subsurface layer, caused by eddy−induced vertical displacements of the isopycnal surfaces. In the eddy core, the maximum temperature anomalies induced by a cyclonic eddy (CE) and an anticyclonic eddy (AE) are about −1.2 °C and +1.2 °C, respectively. The anomalies are located at approximately 100 m. The corresponding salinity anomalies are located at approximately 50 m with a value of −0.1 psu (0.1 psu) for CE (AE). The eddy thermohaline structure has a seasonal character. A deeper temperature and salinity core occurs in both CE and AE in spring compared to that in other seasons, which is primarily caused by the relatively deep thermocline and halocline during that season. In addition, unique warming anomalies induced by CE are present in the mixed layer during winter due to the vertical advection of the BL (Barrier Layer) warmer water by eddies. The total meridional heat transport induced by the composite eddy is poleward (equatorward) south (north) to 10°N with a value of 0.01 PW (−0.013 PW), whereas the total meridional freshwater transport is equatorward with a value of 0.046 Sv over a one−year period. The volume of freshwater export out of the bay is approximately 35% of the annual net freshwater input from local precipitation and river discharge.
Queue-Aware Beam Scheduling for Half-Duplex mmWave Relay Networks

We focus on two basic millimeter wave (mmWave) relay networks and for each network, we propose three beam scheduling methods to approach the network information theoretic capacity. The proposed beam scheduling methods include the deterministic horizontal continuous edge coloring (HC-EC) scheduler, the adaptive back pressure (BP) scheduler and the adaptive low-delay new back pressure (newBP) scheduler. With the aid of computer simulations, we show that within the network capacity range, the proposed schedulers provide good guarantees for the network stability, meanwhile achieve very low packet end-to-end delay.
DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-Based Robotic Grasping

This article presents a method for grasping novel objects by learning from experience. Successful attempts are remembered and then used to guide future grasps such that more reliable grasping is achieved over time. To transfer the learned experience to unseen objects, we introduce the dense geometric correspondence matching network (DGCM-Net). This applies metric learning to encode objects with similar geometry nearby in feature space. Retrieving relevant experience for an unseen object is thus a nearest neighbor search with the encoded feature maps. DGCM-Net also reconstructs 3D-3D correspondences using the view-dependent normalized object coordinate space to transform grasp configurations from retrieved samples to unseen objects. In comparison to baseline methods, our approach achieves an equivalent grasp success rate. However, the baselines are significantly improved when fusing the knowledge from experience with their grasp proposal strategy. Offline experiments with a grasping dataset highlight the capability to transfer grasps to new instances as well as to improve success rate over time from increasing experience. Lastly, by learning task-relevant grasps, our approach can prioritize grasp configurations that enable the functional use of objects.
Credit Scoring Using Machine Learning by Combing Social Network Information: Evidence from Peer-to-Peer Lending

Financial institutions use credit scoring to evaluate potential loan default risks. However, insufficient credit information limits the peer-to-peer (P2P) lending platform’s capacity to build effective credit scoring. In recent years, many types of data are used for credit scoring to compensate for the lack of credit history data. Whether social network information can be used to strengthen financial institutions’ predictive power has received much attention in the industry and academia. The aim of this study is to test the reliability of social network information in predicting loan default. We extract borrowers’ social network information from mobile phones and then use logistic regression to test the relationship between social network information and loan default. Three machine learning algorithms—random forest, AdaBoost, and LightGBM—were constructed to demonstrate the predictive performance of social network information. The logistic regression results show that there is a statistically significant correlation between social network information and loan default. The machine learning algorithm results show that social network information can improve loan default prediction performance significantly. The experiment results suggest that social network information is valuable for credit scoring.
New SARS-like virus in China triggers alarm.

The discovery that a novel, SARS-like coronavirus explains a cluster of pneumonia cases in Wuhan, China, now allows public health officials worldwide to identify infected people and contain the spread. But the virus, which closely resembles four bat coronaviruses that can infect human cells, has left researchers scrambling to answer many questions. One is the extent of spread, and a case of a Wuhan tourist in Thailand who was detected to have the disease underscores that it has the ability to travel quickly outside of the Chinese megacity. It also remains unclear which animals in the Wuhan seafood market are linked to the outbreak. Although no evidence exists of human-to-human transmission, the Chinese tourist in Thailand and a few of the other infected people in Wuhan say they did not visit the seafood market. Only one of 42 people who have confirmed cases of the disease has died, and he had serious underlying health issues. After criticism surfaced about potential delays in sharing information, Chinese scientists have made six sequences of the virus available, which has allowed other researchers to rapidly develop diagnostic tests and begin synthesizing the virus so it can be studied in animal markets. A major concern is the upcoming Lunar New Year on 25 January, during which hundreds of millions of people travel around the country and could potentially spread the infection.
Bootstrap-Optimised Regularised Image Reconstruction for Emission Tomography

In emission tomography, iterative image reconstruction from noisy measured data usually results in noisy images, and so regularisation is often used to compensate for noise. However, in practice, an appropriate, automatic and precise specification of the strength of regularisation for image reconstruction from a given noisy measured dataset remains unresolved. Existing approaches are either empirical approximations with no guarantee of generalisation, or else are computationally intensive cross-validation methods requiring full reconstructions for a limited set of preselected regularisation strengths. In contrast, we propose a novel methodology embedded within iterative image reconstruction, using one or more bootstrapped replicates of the measured data for precise optimisation of the regularisation. The approach uses a conventional unregularised iterative update of a current image estimate from the noisy measured data, and then also uses the bootstrap replicate to obtain a bootstrap update of the current image estimate. The method then seeks the regularisation hyperparameters which, when applied to the bootstrap update of the image, lead to a best fit of the regularised bootstrap update to the conventional measured data update. This corresponds to estimating the degree of regularisation needed in order to map the noisy update to a model of the mean of an ensemble of noisy updates. For a given regularised objective function (e.g. penalised likelihood), no hyperparameter selection or tuning is required. The method is demonstrated for positron emission tomography (PET) data at different noise levels, and delivers near-optimal reconstructions (in terms of reconstruction error) without any knowledge of the ground truth, nor any form of training data.
BF12, a Novel Benzofuran, Exhibits Antitumor Activity by Inhibiting Microtubules and the PI3K/Akt/mTOR Signaling Pathway in Human Cervical Cancer Cells

BF12 [(2E)‐3‐[6‐Methoxy‐2‐(3,4,5‐trimethoxybenzoyl)‐1‐benzofuran‐5‐yl]prop‐2‐enoic acid], a novel derivative of combretastatin A‐4 (CA‐4), was previously found to inhibit tumor cell lines, with a particularly strong inhibitory effect on cervical cancer cells. In this study, we investigated the microtubule polymerization effects and apoptosis signaling mechanism of BF12. BF12 showed a potent efficiency against cervical cancer cells, SiHa and HeLa, with IC50 values of 1.10 and 1.06 μm, respectively. The cellular mechanism studies revealed that BF12 induced G2/M phase arrest and apoptosis in SiHa and HeLa cells, which were associated with alterations in the expression of the cell G2/M cycle checkpoint‐related proteins (cyclin B1 and cdc2) and alterations in the levels of apoptosis‐related proteins (P53, caspase‐3, Bcl‐2, and Bax) of these cells, respectively. Western blot analysis showed that BF12 inhibited the PI3 K/Akt/mTOR signaling pathway and induced apoptosis in human cervical cancer cells. BF12 was identified as a tubulin polymerization inhibitor, evidenced by the effective inhibition of tubulin polymerization and heavily disrupted microtubule networks in living SiHa and HeLa cells. By inhibiting the PI3 K/Akt/mTOR signaling pathway and inducing apoptosis in human cervical cancer cells, BF12 shows promise for use as a microtubule inhibitor.
Denture Wearing and Malnutrition Risk Among Community-Dwelling Older Adults

Most studies have associated denture wearing with a higher risk of malnutrition and lower nutritional intake in the elderly. As the effect of wearing dentures remains debatable, the aim of this study was to determine if older adults wearing dentures have a higher risk of malnutrition. We recruited 294 Japanese community-dwelling adults aged ≥65 years from two elderly welfare centers in Sapporo. The Mini Nutritional Assessment-Short Form (MNA-SF) was used to assess their nutritional status. Their demographic characteristics, eating habits, and health status were assessed using a questionnaire. Moreover, salt-impregnated taste paper and bioelectrical impedance analysis were used to obtain salt taste sensitivity and body composition (body mass index and protein mass). The mean age of older adults was 75.8 ± 5.8 years and 71.1% were women. We found that 74.1% of the older adults wore dentures. The proportion of the whole population with a risk of malnutrition was 23.5%. Multivariate analysis revealed that partial denture wearing could be protective against the risk of malnutrition. In this study, we found more partial denture wearers with normal nutritional conditions and cooking by themselves than non-denture-wearing older adults. Furthermore, complete denture wearers were eating significantly less meats or fish every day. This study suggests that using partial dentures to replace the lost teeth to meet the dietary needs of the elderly is critical to maintaining a healthy nutritional status. Moreover, it also indicates the importance of providing education to older adults who wear complete dentures.