Miracle-dz/UniFAR-FTUs huggingface dataset:
The Global Pregnancy Collaboration (CoLab) symposium on short- and long-term outcomes in offspring whose mothers had preeclampsia: A scoping review of clinical evidence

Preeclampsia is a maternal syndrome characterized by the new onset of hypertension after 20 weeks of gestation associated with multisystemic complications leading to high maternal and fetal/neonatal morbidity and mortality. However, sequelae of preeclampsia may extend years after pregnancy in both mothers and their children. In addition to the long-term adverse cardiovascular effects of preeclampsia in the mother, observational studies have reported elevated risk of cardiovascular, metabolic, cerebral and cognitive complications in children born from women with preeclampsia. Less clear is whether the association between maternal preeclampsia and offspring sequelae are causal, or to what degree the associations might be driven by fetal factors including impaired growth and the health of its placenta. Our discussion of these complexities in the 2018 Global Pregnancy Collaboration annual meeting prompted us to write this review. We aimed to summarize the evidence of an association between maternal preeclampsia and neurobehavioral developmental disorders in offspring in hopes of generating greater research interest in this important topic.
Identification of hepatoprotective traditional Chinese medicines based on the structure–activity relationship, molecular network, and machine learning techniques

The efforts focused on discovering potential hepatoprotective drugs are critical for relieving the burdens caused by liver diseases. Traditional Chinese medicine (TCM) is an important resource for discovering hepatoprotective agents. Currently, there are hundreds of hepatoprotective products derived from TCM available in the literature, providing crucial clues to discover novel potential hepatoprotectants from TCMs based on predictive research. In the current study, a large-scale dataset focused on TCM-induced hepatoprotection was established, including 676 hepatoprotective ingredients and 205 hepatoprotective TCMs. Then, a comprehensive analysis based on the structure–activity relationship, molecular network, and machine learning techniques was performed at molecular and holistic TCM levels, respectively. As a result, we developed an in silico model for predicting the hepatoprotective activity of ingredients derived from TCMs, in which the accuracy exceeded 85%. In addition, we originally proposed a material basis and a drug property-based approach to identify potential hepatoprotective TCMs. Consequently, a total of 12 TCMs were predicted to hold potential hepatoprotective activity, nine of which have been proven to be beneficial to the liver in previous publications. The high rate of consistency between our predictive results and the literature reports demonstrated that our methods were technically sound and reliable. In summary, systematical predictive research focused on the hepatoprotection of TCM was conducted in this work, which would not only assist screening of potential hepatoprotectants from TCMs but also provide a novel research mode for discovering the potential activities of TCMs.
In silico prediction of the animal susceptibility and virtual screening of natural compounds against SARS-CoV-2: Molecular dynamics simulation based analysis

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It has six open reading frames (orf1ab, orf3a, orf6, orf7a, orf8, and orf10), a spike protein, a membrane protein, an envelope small membrane protein, and a nucleocapsid protein, out of which, orf1ab is the largest ORF coding different important non-structural proteins. In this study, an effort was made to evaluate the susceptibility of different animals against SARS-CoV-2 by analyzing the interactions of Spike and ACE2 proteins of the animals and propose a list of potential natural compounds binding to orf1ab of SARS-CoV-2. Here, we analyzed structural interactions between spike proteins of SARS-CoV-2 and the ACE2 receptor of 16 different hosts. A simulation for 50 ns was performed on these complexes. Based on post-simulation analysis, Chelonia mydas was found to have a more stable complex, while Bubalus bubalis, Aquila chrysaetos chrysaetos, Crocodylus porosus, and Loxodonta africana were found to have the least stable complexes with more fluctuations than all other organisms. Apart from that, we performed domain assignment of orf1ab of SARS-CoV-2 and identified 14 distinct domains. Out of these, Domain 3 (DNA/RNA polymerases) was selected as a target, as it showed no similarities with host proteomes and was validated in silico. Then, the top 10 molecules were selected from the virtual screening of ∼1.8 lakh molecules from the ZINC database, based on binding energy, and validated for ADME and toxicological properties. Three molecules were selected and analyzed further. The structural analysis showed that these molecules were residing within the pocket of the receptor. Finally, a simulation for 200 ns was performed on complexes with three selected molecules. Based on post-simulation analysis (RMSD, RMSF, Rg, SASA, and energies), the molecule ZINC000103666966 was found as the most suitable inhibitory compound against Domain 3. As this is an in silico prediction, further experimental studies could unravel the potential of the proposed molecule against SARS-CoV-2.
Differentiation of different stages of brain tumor infiltration using optical coherence tomography: Comparison of two systems and histology

The discrimination of tumor-infiltrated tissue from non-tumorous brain tissue during neurosurgical tumor excision is a major challenge in neurosurgery. It is critical to achieve full tumor removal since it directly correlates with the survival rate of the patient. Optical coherence tomography (OCT) might be an additional imaging method in the field of neurosurgery that enables the classification of different levels of tumor infiltration and non-tumorous tissue. This work investigated two OCT systems with different imaging wavelengths (930 nm/1310 nm) and different resolutions (axial (air): 4.9 μm/16 μm, lateral: 5.2 μm/22 μm) in their ability to identify different levels of tumor infiltration based on freshly excised ex vivo brain samples. A convolutional neural network was used for the classification. For both systems, the neural network could achieve classification accuracies above 91% for discriminating between healthy white matter and highly tumor infiltrated white matter (tumor infiltration >60%) . This work shows that both OCT systems with different optical properties achieve similar results regarding the identification of different stages of brain tumor infiltration.
Implemented occupational health surveillance limits the spread of SARS-CoV-2 Omicron at the workplace

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has put an enormous pressure on human societies, at both health and economic levels. Early diagnosis of SARS-CoV-2, the causative agent of 2019 coronavirus disease (COVID-19), has proved an efficient method to rapidly isolate positive individuals and reduce transmission rates, thus alleviating its negative impact on society’s well-being and economic growth. In this work, through a coordinated and centralized effort to monitor SARS-CoV-2 circulation in companies from the State of Rio de Janeiro, Brazil, we have detected and linked an early rise of infection rates in January 2022 to the introduction of the Omicron variant of concern (VoC) (BA.1). Interestingly, when the Omicron genomic isolates were compared to correlates from public datasets, it was revealed that introduction events were multiple, with possible migration routes mapping to: Mali; Oman and United States; and Italy, Latin America, and United States. In addition, we have built a haplotype network with our genomic dataset and found no strong evidence of transmission chains, between and within companies. Considering Omicron’s particularly high transmissibility, and that most of our samples (>87%) arose from 3 out of 10 companies, these findings suggest that workers from such environments were exposed to SARS-CoV-2 outside their company boundaries. Thus, using a mixed strategy in which quick molecular diagnosis finds support in comprehensive genomic analysis, we have shown that a successfully implemented occupational health program should contribute to document emerging VoC and to limit the spread of SARS-CoV-2 at the workplace.
Examination of the role of necroptotic damage-associated molecular patterns in tissue fibrosis

Fibrosis is defined as the abnormal and excessive deposition of extracellular matrix (ECM) components, which leads to tissue or organ dysfunction and failure. However, the pathological mechanisms underlying fibrosis remain unclear. The inflammatory response induced by tissue injury is closely associated with tissue fibrosis. Recently, an increasing number of studies have linked necroptosis to inflammation and fibrosis. Necroptosis is a type of preprogrammed death caused by death receptors, interferons, Toll-like receptors, intracellular RNA and DNA sensors, and other mediators. These activate receptor-interacting protein kinase (RIPK) 1, which recruits and phosphorylates RIPK3. RIPK3 then phosphorylates a mixed lineage kinase domain-like protein and causes its oligomerization, leading to rapid plasma membrane permeabilization, the release of cellular contents, and exposure of damage-associated molecular patterns (DAMPs). DAMPs, as inflammatory mediators, are involved in the loss of balance between extensive inflammation and tissue regeneration, leading to remodeling, the hallmark of fibrosis. In this review, we discuss the role of necroptotic DAMPs in tissue fibrosis and highlight the inflammatory responses induced by DAMPs in tissue ECM remodeling. By summarizing the existing literature on this topic, we underscore the gaps in the current research, providing a framework for future investigations into the relationship among necroptosis, DAMPs, and fibrosis, as well as a reference for later transformation into clinical treatment.
A systematic review on omics data (metagenomics, metatranscriptomics, and metabolomics) in the role of microbiome in gallbladder disease

Microbiotas are the range of microorganisms (mainly bacteria and fungi) colonizing multicellular, macroscopic organisms. They are crucial for several metabolic functions affecting the health of the host. However, difficulties hamper the investigation of microbiota composition in cultivating microorganisms in standard growth media. For this reason, our knowledge of microbiota can benefit from the analysis of microbial macromolecules (DNA, transcripts, proteins, or by-products) present in various samples collected from the host. Various omics technologies are used to obtain different data. Metagenomics provides a taxonomical profile of the sample. It can also be used to obtain potential functional information. At the same time, metatranscriptomics can characterize members of a microbiome responsible for specific functions and elucidate genes that drive the microbiotas relationship with its host. Thus, while microbiota refers to microorganisms living in a determined environment (taxonomy of microorganisms identified), microbiome refers to the microorganisms and their genes living in a determined environment and, of course, metagenomics focuses on the genes and collective functions of identified microorganisms. Metabolomics completes this framework by determining the metabolite fluxes and the products released into the environment. The gallbladder is a sac localized under the liver in the human body and is difficult to access for bile and tissue sampling. It concentrates the bile produced in the hepatocytes, which drains into bile canaliculi. Bile promotes fat digestion and is released from the gallbladder into the upper small intestine in response to food. Considered sterile originally, recent data indicate that bile microbiota is associated with the biliary tract’s inflammation and carcinogenesis. The sample size is relevant for omic studies of rare diseases, such as gallbladder carcinoma. Although in its infancy, the study of the biliary microbiota has begun taking advantage of several omics strategies, mainly based on metagenomics, metabolomics, and mouse models. Here, we show that omics analyses from the literature may provide a more comprehensive image of the biliary microbiota. We review studies performed in this environmental niche and focus on network-based approaches for integrative studies.
Priming creativity: Doing math reduces creativity and happiness whereas playing short online games enhance them

Creative thinking is an indispensable cognitive skill that is becoming increasingly important. In the present research, we tested the impact of games on creativity and emotions in a between-subject online experiment with four conditions (N = 658). (1) participants played a simple puzzle game that allowed many solutions (priming divergent thinking); (2) participants played a short game that required one fitting solution (priming convergent thinking); (3) participants performed mental arithmetic; (4) passive control condition. Results show that divergent and convergent creativity were higher after playing games and lower after mental arithmetic. Positive emotions did not function as a mediator, even though they were also heightened after playing the games and lower after mental arithmetic. However, contrary to previous research, we found no direct effect of emotions, creative self-efficacy, and growth- vs. fixed on creative performance. We discuss practical implications for digital learning and application settings.
Unravelling the pharmacokinetics of aflatoxin B1: In vitro determination of Michaelis–Menten constants, intrinsic clearance and the metabolic contribution of CYP1A2 and CYP3A4 in pooled human liver microsomes

Mycotoxins, fungal secondary metabolites, are ubiquitously present in food commodities. Acute exposure to high levels or chronic exposure to low levels has an impact on the human body. The phase I metabolism in the human liver, performed by cytochrome P450 (CYP450) enzymes, is accountable for more than 80% of the overall metabolism of exogenous and endogenous compounds. Mycotoxins are (partially) metabolized by CYP450 enzymes. In this study, in vitro research was performed on CYP450 probes and aflatoxin B1 (AFB1), a carcinogenic mycotoxin, to obtain pharmacokinetic data on AFB1, required for further experimental work. The CYP450 probes of choice were a CYP3A4 substrate, midazolam (MDZ) and a CYP1A2 substrate, phenacetin (PH) since these are the main metabolizing phase I enzymes of AFB1. Linearity experiments were performed on the three substrates indicating that linear conditions were achieved at a microsomal protein concentration and incubation time of 0.25 mg/ml and 5 min, 0.50 mg/ml and 20 min and 0.25 mg/ml and 5 min for MDZ, PH and AFB1, respectively. The Km was determined in human liver microsomes and was estimated at 2.15 μM for MDZ, 40.0 μM for PH and 40.9 μM for AFB1. The associated Vmax values were 956 pmol/(mg.min) (MDZ), 856 pmol/(mg.min) (PH) and 11,536 pmol/(mg.min) (AFB1). Recombinant CYP systems were used to determine CYP450-specific Michaelis–Menten values for AFB1, leading to a CYP3A4 Km of 49.6 μM and an intersystem extrapolation factor (ISEF) corrected Vmax of 43.6 pmol/min/pmol P450 and a CYP1A2 Km of 58.2 μM and an ISEF corrected Vmax of 283 pmol/min/pmol P450. An activity adjustment factor (AAF) was calculated to account for differences between microsome batches and was used as a correction factor in the determination of the human in vivo hepatic clearance for MDZ, PH and AFB1. The hepatic blood clearance corrected for the AAF CLH,B,MDZ,AAF, CLH,B,PH,AAF CLH,B,AFB1,AAF(CYP3A4) and CLH,B,AFB1,AAF(CYP1A2) were determined in HLM at 44.1 L/h, 21.7 L/h, 40.0 L/h and 38.5 L/h. Finally, inhibition assays in HLM showed that 45% of the AFB1 metabolism was performed by CYP3A4/3A5 enzymes and 49% by CYP1A2 enzymes.
Comparing the social signaling behavior of humpback whales in three group types on the Hawaiian breeding grounds using acoustic tags

Humpback whales (Megaptera novaeangliae) are exceptionally vocal among baleen whale species. While extensive research has been conducted on humpback whale songs, gaps remain in our understanding of other forms of communication, particularly non-song calls. Here, we compare the spectral features and temporal parameters of non-song calls recorded from AcousondeTM tagged humpback whales in three commonly observed group types in the breeding grounds: adult dyads (N = 3), singly escorted mother-calf pairs (N = 4), and competitive groups (N = 4). Recordings were collected off Maui, Hawai’i during the winter breeding seasons of 2019–2021. Individual calls were identified based on visual and aural inspection of spectrograms using Raven Pro 1.6 software, with a total of 842 calls isolated from 47.6 h of acoustic recordings. Competitive groups produced the most calls (N = 358); however, after adjusting for the differences in recording hours and the number of individuals, the call rate (calls/hour/whale) was not significantly different between group compositions. The temporal parameters and frequency measures of calls did not vary significantly across the groups. However, interesting patterns of calling behavior were observed (e.g., competitive groups had the shortest inter-call intervals and the highest frequency calls, and escorted mother-calf pairs had the longest inter-call intervals) and it is possible the lack of statistical significance could be attributed to the small sample size of tag deployments. This study provides new insights into humpback whale vocal communication behavior in the Hawaiian Islands breeding grounds.
A novel method to purify small RNAs from human tissues for methylation analysis by LC-MS/MS

Methylation modification of small RNAs, including miRNA, piRNA, and tsRNA, is critical for small RNA biogenesis and biological function. Methylation of individual small RNA can be defined by liquid chromatography-coupled with mass spectrometry (LC-MS/MS). However, LC-MS/MS analysis requires a high purity of individual small RNA. Due to the difficulty of purifying specific small RNA from tissues or cells, the progress in characterizing small RNA methylation by LC-MS/MS is limited. Here, we report a novel method that can efficiently purify small RNA from human tissues for LC-MS/MS analysis. This method includes two steps: 1) pull down the target small RNA by incubating total small RNAs (18–24 nt) extracted from human tissues with a biotinylated antisense oligonucleotide of the target small RNA, followed by capturing the binding duplex of biotinylated antisense and small RNA via streptavidin magnetic beads, and 2) protect the target small RNA by pairing it with a single-strand DNA, which sequence is complementary to the target small RNA, to form a DNA/RNA hybrid double-strand, followed by sequential digestion with exonuclease I, nuclease S1, and DNase I, respectively. Furthermore, employing a mixture of four pairs of synthetic methylated and non-methylated small RNAs, we further refined this two-step method by optimizing the nuclease S1 treatment condition. With this method, we successfully purified miR-21-5p, miR-26-5p, piR-020485, and tsRNA from human lung and sperm tissue samples and analyzed their 2′-O-methylation modification at the 3′-end by LC-MS/MS.
Regulation of body weight and food intake by AGRP neurons during opioid dependence and abstinence in mice

Dysregulation of body weight maintenance and opioid dependence are often treated as independent disorders. Here, we assessed the effects of both acute and long-term administration of morphine with and without chemogenetic activation of agouti-related peptide (AGRP)-expressing neurons in the arcuate nucleus (ARCAGRP neurons) to elucidate whether morphine and neuronal activation affect feeding behavior and body weight. First, we characterized interactions of opioids and energy deficit in wild-type mice. We observed that opioid administration attenuated both fasting-induced refeeding and ghrelin-stimulated feeding. Moreover, antagonism of opioid receptors blocked fasting-induced refeeding behavior. Next, we interfaced chemogenetics with opioid dependence. For chemogenetic experiments of ARCAGRP neurons, we conducted a priori behavioral qualification and post-mortem FOS immunostaining verification of arcuate activation following ARCAGRP chemogenetic activation. We administered clozapine during short-term and long-term morphine administration paradigms to determine the effects of dependence on food intake and body weight. We found that morphine occluded feeding behavior characteristic of chemogenetic activation of ARCAGRP neurons. Notably, activation of ARCAGRP neurons attenuated opioid-induced weight loss but did not evoke weight gain during opioid dependence. Consistent with these findings, we observed that morphine administration did not block fasting-induced activation of the ARC. Together, these results highlight the strength of opioidergic effects on body weight maintenance and demonstrate the utility of ARCAGRP neuron manipulations as a lever to influence energy balance throughout the development of opioid dependence.
Isotropy frequency-domain extension imaging and its application in detection of nanostructures

A wide-field high resolution microscopy with sub-micron resolution and high contrast image was demonstrated by using the isotropy frequency-domain extension imaging (IFEI), which was successfully applied to submicron-scale structure detection of fused silica wafer for the first time. Employing the frequency-domain extension and the isotropic period matching, the IFEI extended the bandwidth of coherent transfer function of the conventional wide-field microscopy, thereby improving the resolution to break the diffraction limit. In this method, a quantitative measurement of 200 nm was achieved using fused silica wafer with prefabricated etched structure on the surface. By imaging 81 nm gold nanoparticles, the system resolution calibration was achieved. And corresponding system’s lateral resolution of approximately 179.5 nm was obtained, which was 1.72 times higher than the conventional wide-field microscopy image. Moreover, the reconstructed IFEI images of ultra-precision processed fused silica optics were demonstrated to present the finer structures of sub-micron digs and scratches formed in the optics manufacturing process.
Dengue Fever Responses in Dhaka City, Bangladesh: A Cross-Sectional Survey

Objectives: This study intends to evaluate the Dhaka city residents’ individual views toward DF. Methods: A cross-sectional survey used google forms for collecting data. Python and RStudio were used for data management and analysis. Kruskal-Wallis or Mann-Whitney U test and logistic regression models were performed, where appropriate. Results: In total 1008 individuals participated in a pre-tested KAP survey. More than 20% reported being affected by DF before the survey, where they rated their current places as being moderately safe (43%). In terms of DF control, 65% had good knowledge, and 68% reported good practice, whereas they demonstrated an overall good attitude. The increased knowledge of individuals could contribute to behavioral changes regarding DF. Female residents demonstrated better DF attitudes (OR: 0.69; p < 0.05) and practices (OR: 0.66; p < 0.01) compared to male residents. Mixed unit residents had poor KAP levels. Educational attainment can also play an essential role in enhancing the attitude level. Conclusion: Overall, dengue surveillance activities with sufficient campaigns are required for behavioral change in Dhaka city. This information could be integrated into other DF-affected countries’ strategies against dengue outbreaks.