Miracle-dz/UniFAR-FTUs huggingface dataset:
Host and Bacterial Iron Homeostasis, an Underexplored Area in Tuberculosis Biomarker Research

Mycobacterium tuberculosis (Mtb) “a human adapted pathogen” has found multiple ways to manipulate the host immune response during infection. The human immune response to Mtb infection is a highly complex cascade of reactions, with macrophages as preferred intracellular location. Interaction with the host through infection gives rise to expression of specific gene products for survival and multiplication within the host. The signals that the pathogens encounter during infection cause them to selectively express genes in response to signals. One strategy to identify Mtb antigens with diagnostic potential is to identify genes that are specifically induced during infection or in specific disease stages. The shortcomings of current immunodiagnostics include the failure to detect progression from latent infection to active tuberculosis disease, and the inability to monitor treatment efficacy. This highlights the need for new tuberculosis biomarkers. These biomarkers should be highly sensitive and specific diagnosing TB infection, specifically distinguishing between latent infection and active disease. The regulation of iron levels by the host plays a crucial role in the susceptibility and outcome of Mtb infection. Of interest are the siderophore biosynthetic genes, encoded by the mbt-1 and mbt-2 loci and the SUF (mobilization of sulphur) operon (sufR-sufB-sufD-sufC-csd-nifU-sufT), which encodes the primary iron-sulphur cluster biogenesis system. These genes are induced during iron limitation and intracellular growth of Mtb, pointing to their importance during infection.
MiR-181a Targets RSPO2 and Regulates Bone Morphogenetic Protein – WNT Signaling Crosstalk During Chondrogenic Differentiation of Mesenchymal Stromal Cells

Mechanisms of WNT and bone morphogenetic protein (BMP) signaling crosstalk is in the focus of multiple biological studies, and it also has been discovered to play important roles in human mesenchymal stromal cells (MSC) that are of great interest for neocartilage engineering due to their high chondrogenic differentiation potential. However, MSC-derived chondrocytes undergo hypertrophic degeneration that impedes their clinical application for cartilage regeneration. In our previous study, we established that several microRNAs (miRs) are differentially expressed between articular chondrocytes (AC) – and MSC-derived neocartilage, with miR-181a being the most prominent candidate as key microRNA involved in the regulation of a balance between chondral and endochondral differentiation. The aim of this study was the identification of precise mRNA targets and signaling pathways regulated by miR-181a in MSC during chondrogenesis. MiR-181a was upregulated during chondrogenesis of MSC, along with an increase of the hypertrophic phenotype in resulting cartilaginous tissue. By in silico analysis combined with miR reporter assay, the WNT signaling activator and BMP signaling repressor RSPO2 was suggested as a target of miR-181a. Further validation experiments confirmed that miR-181a targets RSPO2 mRNA in MSC. It was found that in human MSC miR-181a activated BMP signaling manifested by the accumulation of SOX9 protein and increased phosphorylation of SMAD1/5/9. These effects, together with the concomitant reduction of canonical WNT signaling induced by miR-181a mimic, were in accordance with the effects expected by the loss of RSPO2, thus indicating the causative link between miR-181a and RSPO2. Moreover, we observed that a tight correlation between miR-181a and miR-218 expression levels in healthy human cartilage tissue was disrupted in osteoarthritis (OA) highlighting the importance of the WNT-BMP signaling crosstalk for preventing OA.
Characterizing Sex Differences in Depressive-Like Behavior and Glial Brain Cell Changes Following Peripheral Nerve Injury in Mice

Chronic pain and depression are intimately linked; the combination of the two leads to higher health care costs, lower quality of life, and worse treatment outcomes with both conditions exhibiting higher prevalence among women. In the current study, we examined the development of depressive-like behavior in male and female mice using the spared nerve injury (SNI) model of neuropathic pain. Males displayed increased immobility on the forced-swim test – a measure of depressive-like behavior – 2 weeks following injury, while females developed depressive-like behavior at 3-week. Since the pathogenesis of chronic pain and depression may involve overlapping mechanisms including the activation of microglial cells, we explored glial cell changes in brain regions associated with pain processing and affect. Immunohistochemical analyses revealed that microglial cells were more numerous in female SNI mice in the contralateral ventral anterior cingulate cortex (ACC), a brain region important for pain processing and affect behavior, 2-week following surgery. Microglial cell activation was not different between any of the groups for the dorsal ACC or nucleus accumbens. Analysis of astrocyte density did not reveal any significant changes in glial fibrillary acidic protein (GFAP) staining in the ACC or nucleus accumbens. Overall, the current study characterized peripheral nerve injury induced depression-like behavior in male and female mice, which may be associated with different patterns of glial cell activation in regions important for pain processing and affect.
Atezolizumab Plus Chemotherapy vs. Chemotherapy in Advanced or Metastatic Triple-Negative Breast Cancer: A Cost-Effectiveness Analysis

Purpose: The IMpassion130 trial demonstrated the efficacy of adding atezolizumab to paclitaxel for advanced or metastatic triple-negative breast cancer (TNBC). The current study evaluated the cost-effectiveness of adding atezolizumab to nab-paclitaxel for TNBC from the perspective of Chinese health sector. Methods: A partitioned survival model was implemented for patients with TNBC. The survival data were derived from IMpassion130 trial. Direct costs and utility values were collected from the Chinese Drug Bidding Database and published literatures. The primary analysis outcomes were quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). Sensitivity analyses were performed to observe model stability. Results: In the base-case analysis, the ICER of atezolizumab plus nab-paclitaxel vs. nab-paclitaxel is respectively, $176,056/QALY, $118,146/QALY, and $323,077/QALY in the ITT, PD-L1(+) and PD-L1(–) group. Conclusion: Adding atezolizumab to nab-paclitaxel could improve survival time significantly in the PD-L1-positive group, but it is not a cost-effective strategy compared to nab-paclitaxel monotherapy for Chinese patients with advanced or metastatic triple-negative breast cancer in the current economic context of China.
SC75741, A Novel c-Abl Inhibitor, Promotes the Clearance of TDP25 Aggregates via ATG5-Dependent Autophagy Pathway

Abnormal accumulation of TDP43-related mutant proteins in the cytoplasm causes amyotrophic lateral sclerosis (ALS). Herein, unbiased drug screening approaches showed that SC75741, a multi-target inhibitor, inhibited inflammation-induced aggregation by inhibiting NF-κB and also degraded already aggregated proteins by inhibiting c-Abl mediated autophagy-lysosomal pathway. We delineate the mechanism that SC75741 could markedly enhance TFEB nuclear translocation by an mTORC1-independent TFEB regulatory pathway. In addition, SC75741 enhanced the interaction between p62 with TDP25 and LC3C, thus promoting TDP25 degradation. Taken together, these findings show that SC75741 has beneficial neuroprotective effects in ALS. Our study elucidates that dual-targeted inhibition of c-Abl and NF-κB may be a potential treatment for TDP43 proteinopathies and ALS.
Blood Pressure and T-Tau in Spinal Fluid Are Associated With Delayed Recall in Participants With Memory Complaints and Dementia of the Alzheimer’s Type

Objective: The aim of the study was to determine if systolic blood pressure (SBP), total-tau (t-tau), and beta-amyloid (Aβ) in the cerebral spinal fluid (CSF) were associated with the results on the Consortium to Establish a Registry for Alzheimer’s Disease Word List (CERAD-WL) immediate and delayed recall, and the Mini Mental State Examination (MMSE) in “younger” older adults, controlling for age and sex. Method: We included 72 participants, mean age: 62.9 (SD 8.6, range 41–76) from a Norwegian memory clinic; eight were diagnosed with subjective cognitive decline, 32 with mild cognitive impairment (MCI), 30 with dementia of the Alzheimer’s type (DAT), and two with combined DAT and vascular dementia (VaD). Data were examined in three fitted multiple linear regression models using the CERAD-WL immediate and delayed recall, and MMSE as dependent variables; and SBP, t-tau, and Aβ as independent variables, controlling for age and sex. Results: The strongest associations were found in the model using CERAD-WL delayed recall as the dependent variable, where 45% of the variance was explained (standardized Beta = −0.313, p = 0.004 for t-tau and standardized Beta −0.238, p = 0.01 for SBP). The unique contribution of age was close to 8%, t-tau close to 7%, and SBP above 5%. When cardiovascular medication was entered into the analysis, the explained variance increased to 51% and Aβ became significant (standardized Beta = 0.216, p = 0.03). Participants on this medication exhibited worse performance on CERAD-WL delayed recall than those who were not on medication. Age (7%), t-tau (6%), and SBP (5%) showed the same unique contribution, whereas medication contributed 6% and Aβ contributed 4%. CERAD-WL immediate recall, and MMSE yielded similar findings, but explained variance was poorer for these two variables. Conclusions: Both elevated SBP and t-tau were associated with poorer cognitive performance, especially delayed recall. Those on cardiovascular medication were more impaired than were participants who were not on this medication—a finding that probably reflected cerebral incidents in the medicated group.
The Gradient of Immune/Inflammatory Response and COVID-19 Prognosis with Therapeutic Implications

As of October 8, 2021, there were 236,599,025 confirmed cases and 4,831,486 deaths attributed to COVID-19 (https://covid19.who.int/). The COVID-19 pandemic puts high pressure on medical resources worldwide (1). To reduce the clinical burden and casualties caused by COVID-19, it is urgent to investigate which patients are at high risk and thus in imminent need of critical care services. Hemogram characteristics hold great promise for predicting the clinical outcomes of COVID-19 (2). However, there is still a scarcity of data modeling the gradient of hemogram parameter as a continuous risk predictor of COVID-19 prognosis. Through leveraging the hemogram data of 485 COVID-19 patients and analyzing the pointwise prognostic values across continuous biological and clinical indices, we explored the nonlinear relationship between the continuous hemogram values and their prognostic associations with COVID-19. The immune/inflammatory markers — lymphocytes (%), neutrophils (%), and high-sensitivity Creactive protein (hs-CRP, mg/l) — were significantly associated with the overall survival (OS) of COVID-19 patients in dose-dependent manners. This study shed light on the dose-dependent effects of immune and inflammatory responses on the prognosis of COVID-19 patients, with important implications in immunomodulation and anti-inflammatory therapies for COVID-19. Moreover, our analytical framework will help better delineate clinical predictors for not only COVID-19 but also other human diseases and facilitate the discovery of biomarker and disease mechanisms.
A Novel Plant Leaf Patch Absorbed With IL-33 Antibody Decreases Venous Neointimal hyperplasia

Introduction: We recently showed that a decellularized leaf scaffold can be loaded with polylactic-co-glycolic acid (PLGA)-based rapamycin nanoparticles, this leaf patch can then inhibit venous neointimal hyperplasia in a rat inferior vena cava (IVC) venoplasty model. IL-33 plays a role in the neointimal formation after vascular injury. We hypothesized that plant leaves can absorb therapeutic drug solution and can be used as a patch with drug delivery capability, and plant leaves absorbed with IL-33 antibody can decrease venous neointimal hyperplasia in the rat IVC venoplasty model. Method: A human spiral saphenous vein (SVG) graft implanted in the popliteal vein was harvested from a patient with trauma and analyzed by immunofluorescence. Male Sprague-Dawley rats (aged 6–8 weeks) were used to create the IVC patch venoplasty model. Plant leaves absorbed with rhodamine, distilled water (control), rapamycin, IL-33, and IL-33 antibody were cut into patches (3 × 1.5 mm2) and implanted into the rat IVC. Patches were explanted at day 14 for analysis. Result: At day 14, in the patch absorbed with rhodamine group, immunofluorescence showed rhodamine fluorescence in the neointima, inside the patch, and in the adventitia. There was a significantly thinner neointima in the plant patch absorbed with rapamycin (p = 0.0231) compared to the patch absorbed with distilled water. There was a significantly large number of IL-33 (p = 0.006) and IL-1β (p = 0.012) positive cells in the human SVG neointima compared to the human great saphenous vein. In rats, there was a significantly thinner neointima, a smaller number of IL-33 (p = 0.0006) and IL-1β (p = 0.0008) positive cells in the IL-33 antibody-absorbed patch group compared to the IL-33-absorbed patch group. Conclusion: We found that the natural absorption capability of plant leaves means they can absorb drug solution efficiently and can also be used as a novel drug delivery system and venous patch. IL-33 plays a role in venous neointimal hyperplasia both in humans and rats; neutralization of IL-33 by IL-33 antibody can be a therapeutic method to decrease venous neointimal hyperplasia.
Integrative Models of Brain Structure and Dynamics: Concepts, Challenges, and Methods

The anatomical architecture of the brain constrains the dynamics of interactions between various regions. On a microscopic scale, neural plasticity regulates the connections between individual neurons. This microstructural adaptation facilitates coordinated dynamics of populations of neurons (mesoscopic scale) and brain regions (macroscopic scale). However, the mechanisms acting on multiple timescales that govern the reciprocal relationship between neural network structure and its intrinsic dynamics are not well understood. Studies empirically investigating such relationships on the whole-brain level rely on macroscopic measurements of structural and functional connectivity estimated from various neuroimaging modalities such as Diffusion-weighted Magnetic Resonance Imaging (dMRI), Electroencephalography (EEG), Magnetoencephalography (MEG), and functional Magnetic Resonance Imaging (fMRI). dMRI measures the anisotropy of water diffusion along axonal fibers, from which structural connections are estimated. EEG and MEG signals measure electrical activity and magnetic fields induced by the electrical activity, respectively, from various brain regions with a high temporal resolution (but limited spatial coverage), whereas fMRI measures regional activations indirectly via blood oxygen level-dependent (BOLD) signals with a high spatial resolution (but limited temporal resolution). There are several studies in the neuroimaging literature reporting statistical associations between macroscopic structural and functional connectivity. On the other hand, models of large-scale oscillatory dynamics conditioned on network structure (such as the one estimated from dMRI connectivity) provide a platform to probe into the structure-dynamics relationship at the mesoscopic level. Such investigations promise to uncover the theoretical underpinnings of the interplay between network structure and dynamics and could be complementary to the macroscopic level inquiries. In this article, we review theoretical and empirical studies that attempt to elucidate the coupling between brain structure and dynamics. Special attention is given to various clinically relevant dimensions of brain connectivity such as the topological features and neural synchronization, and their applicability for a given modality, spatial or temporal scale of analysis is discussed. Our review provides a summary of the progress made along this line of research and identifies challenges and promising future directions for multi-modal neuroimaging analyses.
Toxic Epidermal Necrolysis-Like Reaction Following Combination Therapy With Camrelizumab and Apatinib for Advanced Gallbladder Carcinoma

Recently, combination regimens based on programmed cell death-1 (PD-1) blockade have become increasingly common in clinical practice for the treatment of cancer. Such combinations significantly improve efficacy, but treatment-related adverse events have also become more complex and severe. Here, we report an acute toxic epidermal necrolysis (TEN)-like reaction in a patient with gallbladder cancer who received camrelizumab (an anti-PD-1 antibody) in combination with apatinib. Interestingly, distinct clinical and pathological characteristics were observed that differed from those of the reported cases of severe cutaneous reactions induced by anti-PD-1 antibodies alone; thus, we speculate that it was induced by the combination of camrelizumab and apatinib. It is worth noting that the TEN-like reaction showed resistance to methylprednisolone initially, which was gradually resolved after the addition of intravenous immunoglobulin (IVIg). Immunohistochemical staining revealed that the skin lesion was infiltrated by moderate numbers of CD4+ T cells and large numbers of CD8+ T cells during the progression of the TEN-like reaction, and mass cytometry by time-of-flight showed a significant reduction in the CD4+ and CD8+ T cell proportions in the peripheral blood after the rash improved. All these findings highlight the essential role of CD4+ T cells and CD8+ T cells in the TEN-like reaction induced by camrelizumab plus apatinib treatment, and we speculate that T cells, especially CD8+ T cells, attack keratinocytes. In conclusion, the TEN-like reaction induced by camrelizumab and apatinib deserves clinical attention, and further work is needed to elucidate the exact pathophysiologic mechanism as well as the optimal management strategy.
Development and Validation of Ribosomal RNA-Targeted Reverse Transcription Real-Time PCR Assays for the Sensitive and Rapid Diagnostics of High Consequence Pathogens

Real-time PCR (rtPCR) has become an essential tool in clinical microbiology and has been used for the acute diagnostics of many pathogens. Key performance indicators of rtPCR assays are their specificity as well as their analytical and clinical sensitivity. One way to maximize the sensitivity of such diagnostic rtPCRs is the use of genomic targets, which are present in several copies in the target cells. Here, we use the naturally pre-amplified ribosomal RNA as target for specific and highly sensitive reverse-transcription rtPCR detection of two high consequence pathogens, Yersinia pestis and Francisella tularensis. We determined their analytical sensitivity and illustrate that the newly designed assays are superior compared with other previous published rtPCR assays. Furthermore, we used spiked clinical sample matrices to evaluate their clinical applicability. Finally, we demonstrate that these assays can be applied on heat-inactivated samples without the need of time-consuming nucleic acid extraction.
C4Net: Contextual Compression and Complementary Combination Network for Salient Object Detection

Deep learning solutions of the salient object detection problem have achieved great results in recent years. The majority of these models are based on encoders and decoders, with a different multi-feature combination. In this paper, we show that feature concatenation works better than other combination methods like multiplication or addition. Also, joint feature learning gives better results, because of the information sharing during their processing. We designed a Complementary Extraction Module (CEM) to extract necessary features with edge preservation. Our proposed Excessiveness Loss (EL) function helps to reduce false-positive predictions and purifies the edges with other weighted loss functions. Our designed Pyramid-Semantic Module (PSM) with Global guiding flow (G) makes the prediction more accurate by providing high-level complementary information to shallower layers. Experimental results show that the proposed model outperforms the state-of-the-art methods on all benchmark datasets under three evaluation metrics.
Clustering and Bootstrapping Based Framework for News Knowledge Base Completion

Extracting the facts, namely entities and relations, from unstructured sources is an essential step in any knowledge base construction. At the same time, it is also necessary to ensure the completeness of the knowledge base by incrementally extracting the new facts from various sources. To date, the knowledge base completion is studied as a problem of knowledge refinement where the missing facts are inferred by reasoning about the information already present in the knowledge base. However, facts missed while extracting the information from multilingual sources are ignored. Hence, this work proposed a generic framework for knowledge base completion to enrich a knowledge base of crime-related facts extracted from online news articles in the English language, with the facts extracted from low resourced Indian language Hindi news articles. Using the framework, information from any low-resourced language news articles can be extracted without using language-specific tools like POS tags and using an appropriate machine translation tool. To achieve this, a clustering algorithm is proposed, which explores the redundancy among the bilingual collection of news articles by representing the clusters with knowledge base facts unlike the existing Bag of Words representation. From each cluster, the facts extracted from English language articles are bootstrapped to extract the facts from comparable Hindi language articles. This way of boot-strapping within the cluster helps to identify the sentences from a low-resourced language that are enriched with new information related to the facts extracted from a high-resourced language like English. The empirical result shows that the proposed clustering algorithm produced more accurate and high-quality clusters for monolingual and cross-lingual facts, respectively. Experiments also proved that the proposed framework achieves a high recall rate in extracting the new facts
A Systematic Literature Review on Federated Machine Learning

Federated learning is an emerging machine learning paradigm where clients train models locally and formulate a global model based on the local model updates. To identify the state-of-the-art in federated learning and explore how to develop federated learning systems, we perform a systematic literature review from a software engineering perspective, based on 231 primary studies. Our data synthesis covers the lifecycle of federated learning system development that includes background understanding, requirement analysis, architecture design, implementation, and evaluation. We highlight and summarise the findings from the results and identify future trends to encourage researchers to advance their current work.