Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondria transplantation between living cells

Mitochondria and the complex endomembrane system are hallmarks of eukaryotic cells. To date, it has been difficult to manipulate organelle structures within single live cells. We developed a FluidFM-based approach to extract, inject and transplant organelles from and into living cells with subcellular spatial resolution. The approach enabled the transfer of controlled quantities of mitochondria into cells while maintaining their viability and monitoring their fate in new host cells. Transplantation of healthy and drug-impaired mitochondria into primary keratinocytes allowed real-time tracking of mitochondrial subpopulation rescue. Fusion with the mitochondrial network of recipient cells occurred 20 min after transplantation and continued for over 16 hours. After transfer of mitochondria and cell propagation over generations, we show that donor mtDNA was replicated in recipient cells without the need for selection pressure. The approach opens new prospects for the study of organelle physiology and homeostasis, but also for mechanobiology, synthetic biology, and therapy.
Salmonella Outer Membrane Vesicles contain tRNA Fragments (tRFs) that Inhibit Bacteriophage P22 infection

Salmonella Outer Membrane Vesicles (OMVs) were recently shown to inhibit P22 bacteriophage infection. Furthermore, despite there being several published reports now independently describing (1) the marked prevalence of tRFs within secreted vesicle transcriptomes and (2) roles for specific tRFs in facilitating/inhibiting viral replication, there have been no examinations of the effects of vesicle-secreted tRFs on viral infection reported to date. Notably, while specific tRFs have been reported in a number of bacteria, the tRFs expressed by salmonellae have not been previously characterized. As such, we recently screened small RNA-seq datasets for the presence of recurrent, specifically excised tRFs and identified 31 recurrent, relatively abundant tRFs expressed by Salmonella enterica serovar Typhimurium (SL1344). What’s more, we find S. Typhimurium OMVs contain significant levels of tRFs highly complementary to known Salmonella enterica-infecting bacteriophage with 17 of 31 tRFs bearing marked complementarity to at least one known Salmonella enterica-infecting phage (averaging 97.4% complementarity over 22.9 nt). Most notably, tRNA-Thr-CGT-1-1, 44-73, bears 100% sequence complementary over its entire 30 nt length to 29 distinct, annotated Salmonella enterica-infecting bacteriophage including P22. Importantly, we find inhibiting this tRF in secreted OMVs improves P22 infectivity in a dose dependent manner whereas raising OMV tRF levels conversely inhibits P22 infectivity. Furthermore, we find P22 phage pre-incubation with OMVs isolated from naïve, control SL1344 S. Typhimurium, successfully rescues the ability of S. Typhimurium transformed with a specific tRNA-Thr-CGT-1-1, 44-73 tRF inhibitor to defend against P22. Collectively, these experiments confirm tRFs secreted in S. Typhimurium OMVs are directly involved with and required for the ability of OMVs to defend against bacteriophage predation. As we find the majority of OMV tRFs are highly complementary to an array of known Salmonella enterica-infecting bacteriophage, we suggest OMV tRFs may primarily function as a broadly acting, previously uncharacterized innate antiviral defense.
Oscillations support short latency co-firing of neurons during human episodic memory formation

Theta and gamma oscillations in the medial temporal lobe are suggested to play a critical role for human memory formation via establishing synchrony in neural assemblies. Arguably, such synchrony facilitates efficient information transfer between neurons and enhances synaptic plasticity, both of which benefit episodic memory formation. However, to date little evidence exists from humans that would provide direct evidence for such a specific role of theta and gamma oscillations for episodic memory formation. Here we investigate how oscillations shape the temporal structure of neural firing during memory formation in the medial temporal lobe. We measured neural firing and local field potentials in human epilepsy patients via micro-wire electrode recordings to analyze how brain oscillations promote co-incidences of firing between neurons during successful and unsuccessful encoding of episodic memories. The results show that phase-coupling of neurons to faster theta and gamma oscillations correlates with co-firing at short latencies (∼20-30 ms) and occurs during successful memory formation. Phase-coupling at slower oscillations in these same frequency bands, in contrast, correlates with longer co-firing latencies and occurs during memory failure. Thus, our findings provide evidence which implicate neural oscillations into the synchronization of neural firing in the medial temporal lobe during the encoding of episodic memories.
Do-it-yourself (DIY) furniture for emergency situations: a study on assembling a cardboard bench in Brazil

In emergency situations caused by environmental adversities there is a demand for furniture that should be functional, low cost, easy to assemble and to transport in order to attend the needs for settling the victimised population in improvised shelters. This article discusses the role of procedural pictorial sequences (PPSs) in assembling a do-it-yourself (DIY) cardboard bench for emergency situations in Brazil. An analytical study of PPSs on DIY benches available in Brazil was conducted and an experimental study on comprehention of PPS for cardboard bench and its effects on task performance were carried out with 70 participants. The results showed defficiencies in action representation and in the order of pictures which affected participants understanding and task performance. Some guidelines for designing PPS for DIY benches are also proposed.
Prolactin-Induced Adaptation in Glucose Homeostasis in Mouse Pregnancy Is Mediated by the Pancreas and Not in the Forebrain

Adaptive changes in glucose homeostasis during pregnancy require proliferation of insulin-secreting beta-cells in the pancreas, together with increased sensitivity for glucose-stimulated insulin secretion. Increased concentrations of maternal prolactin/placental lactogen contribute to these changes, but the site of action remains uncertain. Use of Cre-lox technology has generated pancreas-specific prolactin receptor (Prlr) knockouts that demonstrate the development of a gestational diabetic like state. However, many Cre-lines for the pancreas also express Cre in the hypothalamus and prolactin could act centrally to modulate glucose homeostasis. The aim of the current study was to examine the relative contribution of prolactin action in the pancreas and brain to these pregnancy-induced adaptations in glucose regulation. Deletion of prolactin receptor (Prlr) from the pancreas using Pdx-cre or Rip-cre led to impaired glucose tolerance and increased non-fasting blood glucose levels during pregnancy. Prlrl ox/lox /Pdx-Cre mice also had impaired glucose-stimulated insulin secretion and attenuated pregnancy-induced increase in beta-cell fraction. Varying degrees of Prlr recombination in the hypothalamus with these Cre lines left open the possibility that central actions of prolactin could contribute to the pregnancy-induced changes in glucose homeostasis. Targeted deletion of Prlr specifically from the forebrain, including areas of expression induced by Pdx-Cre and Rip-cre, had no effect on pregnancy-induced adaptations in glucose homeostasis. These data emphasize the pancreas as the direct target of prolactin/placental lactogen action in driving adaptive changes in glucose homeostasis during pregnancy.
Genetic Characterization of Brucella spp.: Whole Genome Sequencing-Based Approach for the Determination of Multiple Locus Variable Number Tandem Repeat Profiles

Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.
Neural Activation via Acupuncture in Patients With Major Depressive Disorder: A Functional Near-Infrared Spectroscopy Study

Background and Objective: Acupuncture is used as an alternative treatment for patients with major depressive disorder (MDD). The associated therapeutic effect of acupuncture is often attributed to its modulatory effect on the activity of the pre-frontal cortex (PFC), although the mechanism is not well-studied. We employed a repeated measures design to investigate the brain modulatory effect of acupuncture on the PFC in a group of patients with MDD and investigated whether the modulatory effect is influenced by the severity of the disease. Methods: A total of 47 patients diagnosed with MDD were enrolled in this functional near-infrared spectroscopy experiment. The severity of depressive symptoms was measured at baseline using the Hamilton Depression Rating Scale-24 (HAMD). The cortical activation in the bilateral PFC areas during a verbal fluency task (VFT) was measured before and after a single session of acupuncture in the Baihui acupoint. We further explored the potential correlation between the severity of MDD and task-related activation before and after acupuncture. Results: A single session of acupuncture significantly tended to enhance the activation level of the left frontopolar cortex in patients with severe depression during VFT, but a null effect was found in those with mild to moderate depression. Among patients with severe depression, a strong correlation was observed between HAMD scores and the change in VFT-related activation after acupuncture in the left dorsolateral PFC (DLPFC). Conclusion: A single session of acupuncture did not significantly modulate the activation of the left PFC in patients with mild to moderate depression; however, it demonstrated a tendency to enhance the activation of the frontopolar area in patients with severe depression. Among patients with severe depression, there is a correlation between the activation by acupuncture of left DLPFC during executive functioning and the severity of depressive symptoms, suggesting that the brain activity induced by acupuncture is likely to be influenced by the baseline disease severity in patients with MDD.
Iron Oxide–Modified Carbon Electrode and Sulfate-Reducing Bacteria for Simultaneous Enhanced Electricity Generation and Tannery Wastewater Treatment

The microbial fuel cell (MFC) is emerging as a potential technology for extracting energy from wastes/wastewater while they are treated. The major hindrance in MFC commercialization is lower power generation due to the sluggish transfer of electrons from the biocatalyst (bacteria) to the anode surface and inefficient microbial consortia for treating real complex wastewater. To overcome these concerns, a traditional carbon felt (CF) electrode modification was carried out by iron oxide (Fe3O4) nanoparticles via facile dip-and-dry methods, and mixed sulfate-reducing bacteria (SRBs) were utilized as efficient microbial consortia. In the modified CF electrode with SRBs, a considerable improvement in the bioelectrochemical operation was observed, where the power density (309 ± 13 mW/m2) was 1.86 times higher than bare CF with SRBs (166 ± 11 mW/m2), suggesting better bioelectrochemical performance of an SRB-enriched Fe3O4@CF anode in the MFC. This superior activity can be assigned to the lower charge transfer resistance, higher conductance, and increased number of catalytic sites of the Fe3O4@CF electrode. The SRB-enriched Fe3O4@CF anode also assists in enhancing MFC performance in terms of COD removal (>75%), indicating efficient biodegradability of tannery wastewater and a higher electron transfer rate from SRBs to the conductive anode. These findings demonstrate that a combination of the favorable properties of nanocomposites such as Fe3O4@CF anodes and efficient microbes for treating complex wastes can encourage new directions for renewable energy–related applications.
A Combined Nomogram Model to Predict Disease-free Survival in Triple-Negative Breast Cancer Patients With Neoadjuvant Chemotherapy

Background: To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS. Methods: Patients (n = 150) from two hospitals who received NAC from August 2011 to May 2017 were diagnosed with TNBC by pathological biopsy, and follow-up through May 2020 was retrospectively analysed. Patients from one hospital (n = 109) were used as the training group, and patients from the other hospital (n = 41) were used as the validation group. ROIs were drawn on 1.5 T MRI T1W enhancement images of the whole volume of the tumour obtained with a 3D slicer. Radiomics signatures predicting DFS were identified, optimal cut-off value for Rad-score was determined, and the associations between DFS and radiomics signatures, MRI findings, and clinicopathological variables were analysed. A nomogram was developed and validated for individualized DFS estimation. Results: The median follow-up time was 53.5 months, and 45 of 150 (30.0%) patients experienced recurrence and metastasis. The optimum cut-off value of the Rad-score was 0.2528, which stratified patients into high- and low-risk groups for DFS in the training group (p<0.001) and was validated in the external validation group. Multivariate analysis identified three independent indicators: multifocal/centric disease status, pCR status, and Rad-score. A nomogram based on these factors showed discriminatory ability, the C-index of the model was 0.834 (95% CI, 0.761–0.907) and 0.868 (95% CI, 0.787–949) in the training and the validation groups, respectively, which is better than clinicoradiological nomogram(training group: C-index = 0.726, 95% CI = 0.709–0.743; validation group: C-index = 0.774,95% CI = 0.743–0.805). Conclusion: The Rad-score derived from preoperative MRI features is an independent biomarker for DFS prediction in patients with TNBC to NAC, and the combined radiomics nomogram improved individualized DFS estimation.
Understanding the Antecedents of Knowledge Sharing Behavior From the Theory of Planned Behavior Model: Cross-Cultural Comparisons Between Mainland China and Malaysia

Affected by coronavirus disease (COVID-19), in addition to keeping away the impact of the pandemic on their business practices, many enterprises have proposed relevant measures to protect their employees’ job safety and security. Especially for enterprises with high dependence on knowledge resources, employees’ innovation and knowledge sharing play a vital role. In the context of global economic austerity, how to put forward the corresponding plan of knowledge sharing intention to improve the knowledge sharing behavior of employees for enterprises is worth discussing. Mainland China and Malaysia have different quarantine policies and similar industrial structures. This study examines the awareness of Mainland China vs. Malaysian employees, and evaluates the relationship among self-efficacy, job security, market orientation, knowledge sharing intention, and knowledge sharing behavior from the theory of planned behavior. In this study, a total of 627 Mainland China and 434 Malaysian participants were collected to compare both groups in the development of employees’ knowledge sharing behavior. In this study, a variance-based partial least squares structural equation modeling (PLS-SEM) was performed to test the proposed hypothesis and conduct comparative analysis. The results in both the samples show that self-efficacy, job security, and market orientation have positive and significant effects on knowledge sharing intention; self-efficacy has positive and significant effects on job security; knowledge sharing intention has positive and significant effects on knowledge sharing behavior. Moreover, there are several significant differences between Mainland China and Malaysia in the examinations of path comparisons.
Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

In the last decade, many low-cost monitoring sensors and sensor-networks have been used as an alternative air quality assessment method. It is also well known that these low cost monitors have calibration, accuracy and long term variation problems which require various calibration techniques. In this work PM2.5 and PM10 low cost sensors (Plantower and Nova Fitness) have been tested in five cities under different environmental conditions and compared with collocated standard instruments. Simultaneously, particle composition (organic and black carbon, sulfate, nitrate, chloride, ammonium, and chemical elements) has been measured in the same places to study its influence on the accuracy. The results show a very large variability in the correlation between the low cost sensors and collocated standard instruments depending on the composition and size of particles present in the site. The PM10 correlation coefficient (R 2) between the low cost sensor and a collocated regulatory instrument varied from to 0.95 in Temuco to 0.04 in Los Caleos. PM2.5 correlation varied from 0.97 to 0.68 in the same places. It was found that sites that had higher proportion of large particles had lower correlation between the low cost sensor and the regulatory instrument. Sites that had higher relative concentration of organic and black carbon had better correlation because these species are mostly below the 1 μm size range. Sites that had higher sulfate, nitrate or SiO2 concentrations in PM2.5 or PM10 had low correlation most likely because these particles have a scattering coefficients that depends on its size or composition, thus they can be classified incorrectly.
Diagnostic Model for Discrimination Between Tuberculous Meningitis and Bacterial Meningitis

Background The differential diagnosis between tuberculous meningitis (TBM) and bacterial meningitis (BM) remains challenging in clinical practice. This study aimed to establish a diagnostic model that could accurately distinguish TBM from BM. Methods Patients with TBM or BM were recruited between January 2017 and January 2021 at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort). The detection for indicators involved in cerebrospinal fluid (CSF) and T-SPOT assay were performed simultaneously. Multivariate logistic regression was used to create a diagnostic model. Results A total of 174 patients (76 TBM and 98 BM) and another 105 cases (39 TBM and 66 BM) were enrolled from Qiaokou cohort and Caidian cohort, respectively. Significantly higher level of CSF lymphocyte proportion while significantly lower levels of CSF chlorine, nucleated cell count, and neutrophil proportion were observed in TBM group when comparing with those in BM group. However, receiver operating characteristic (ROC) curve analysis showed that the areas under the ROC curve (AUCs) produced by these indicators were all under 0.8. Meanwhile, tuberculosis-specific antigen/phytohemagglutinin (TBAg/PHA) ratio yielded an AUC of 0.889 (95% CI, 0.840–0.938) in distinguishing TBM from BM, with a sensitivity of 68.42% (95% CI, 57.30%–77.77%) and a specificity of 92.86% (95% CI, 85.98%–96.50%) when a cutoff value of 0.163 was used. Consequently, we successfully established a diagnostic model based on the combination of TBAg/PHA ratio, CSF chlorine, CSF nucleated cell count, and CSF lymphocyte proportion for discrimination between TBM and BM. The established model showed good performance in differentiating TBM from BM (AUC: 0.949; 95% CI, 0.921–0.978), with 81.58% (95% CI, 71.42%–88.70%) sensitivity and 91.84% (95% CI, 84.71%–95.81%) specificity. The performance of the diagnostic model obtained in Qiaokou cohort was further validated in Caidian cohort. The diagnostic model in Caidian cohort produced an AUC of 0.923 (95% CI, 0.867–0.980) with 79.49% (95% CI, 64.47%–89.22%) sensitivity and 90.91% (95% CI, 81.55%–95.77%) specificity. Conclusions The diagnostic model established based on the combination of four indicators had excellent utility in the discrimination between TBM and BM.
Brain Entropy Study on Obsessive-Compulsive Disorder Using Resting-State fMRI

Object: Brain entropy is a potential index in the diagnosis of mental diseases, but there are some differences in different brain entropy calculation, which may bring confusion and difficulties to the application of brain entropy. Based on the resting-state function magnetic resonance imaging (fMRI) we analyzed the differences of the three main brain entropy in the statistical significance, including approximate entropy (ApEn), sample entropy (SampEn) and fuzzy entropy (FuzzyEn), and studied the physiological reasons behind the difference through comparing their performance on obsessive-compulsive disorder (OCD) and the healthy control (HC). Method: We set patients with OCD as the experimental group and healthy subjects as the control group. The brain entropy of the OCD group and the HC are calculated, respectively, by voxel and AAL region. And then we analyzed the statistical differences of the three brain entropies between the patients and the control group. To compare the sensitivity and robustness of these three kinds of entropy, we also studied their performance by using certain signal mixed with noise. Result: Compare with the control group, almost the whole brain's ApEn and FuzzyEn of OCD are larger significantly. Besides, there are more brain regions with obvious differences when using ApEn comparing to using FuzzyEn. There was no statistical difference between the SampEn of OCD and HC. Conclusion: Brain entropy is a numerical index related to brain function and can be used as a supplementary biological index to evaluate brain state, which may be used as a reference for the diagnosis of mental illness. According to an analysis of certain signal mixed with noise, we conclude that FuzzyEn is more accurate considering sensitivity, stability and robustness of entropy.