Miracle-dz/UniFAR-FTUs huggingface dataset:
LMNA Determines Nuclear Morphology During Syncytialization of Human Trophoblast Stem Cells

Upon implantation, the trophectoderm differentiates into the multi-nucleated primitive syncytiotrophoblast (pSTB) through a process called primary syncytialization to facilitate maternal-fetal interactions and to establish a pregnancy. However, ethical issues and limited access to human embryos around the time of embryo implantation hinder the investigation of the detailed molecular mechanisms underpinning this event in humans. Here we established human trophoblast stem cells (hTSCs) from human blastocysts. We characterized nuclear enlargement in STB differentiated from hTSCs, which recapitulate morphological nuclear features of pSTB in human embryos. Specifically, we revealed that CRISPR/Cas9-mediated LMNA disruption perturbated nuclear volume during hTSCs syncytialization. Overall, our results not only provide an interesting insight into mechanisms underlying nuclear enlargement during primary syncytialization but highlight the hTSCs as an indispensable model in understanding human trophoblast differentiation during implantation.
Analysis of ERBB4 Variants in Amyotrophic Lateral Sclerosis Within a Chinese Cohort

ERBB4 is related to amyotrophic lateral sclerosis (ALS) in patients with a family history and is thought to cause ALS-19. We screened 448 ALS patients, including 364 sporadic ALS (sALS) and 84 familial ALS (fALS) patients with ERBB4 variants, in a Chinese cohort. In total, 12 missense variants were identified in this study. Of these, 3 (p.Arg106His, p.Gln164Pro, and p.Val212Leu) were absent from the in-house healthy control cohort and population databases and predicted to be likely pathogenic. Genetic burden analysis did not reveal an increase in damaging variants of the ERBB4 gene. We considered that most of the missense variants in ERBB4 were not pathogenic, but certain variants, such as p.Arg106His, p.Gln164Pro, and p.Val212Leu, were likely pathogenic. The phenotype of these three patients carrying ERBB4 variants revealed the typical clinical manifestations of ALS without cognitive dysfunction. We concluded that ERBB4 likely pathogenic variants account for ~0.67% of ALS patients in China. It is necessary to interpret the relationship between the disease and variants carefully for ALS patients with ERBB4 gene variants.
Transient Effects of Snow Cover Duration on Primary Growth and Leaf Traits in a Tundra Shrub

With the recent climate warming, tundra ecotones are facing a progressive acceleration of spring snowpack melting and extension of the growing season, with evident consequences to vegetation. Along with summer temperature, winter precipitation has been recently recognised as a crucial factor for tundra shrub growth and physiology. However, gaps of knowledge still exist on long-living plant responses to different snowpack duration, especially on how intra-specific and year-to-year variability together with multiple functional trait adjustments could influence the long-term responses. To fill this gap, we conducted a 3 years snow manipulation experiment above the Alpine treeline on the typical tundra species Juniperus communis, the conifer with the widest distributional range in the north emisphere. We tested shoot elongation, leaf area, stomatal density, leaf dry weight and leaf non-structural carbohydrate content of plants subjected to anticipated, natural and postponed snowpack duration. Anticipated snowpack melting enhanced new shoot elongation and increased stomatal density. However, plants under prolonged snow cover seemed to compensate for the shorter growing period, likely increasing carbon allocation to growth. In fact, these latter showed larger needles and low starch content at the beginning of the growing season. Variability between treatments slightly decreased over time, suggesting a progressive acclimation of juniper to new conditions. In the context of future warming scenarios, our results support the hypothesis of shrub biomass increase within the tundra biome. Yet, the picture is still far from being complete and further research should focus on transient and fading effects of changing conditions in the long term.
Neutrophils: Amoeboid Migration and Swarming Dynamics in Tissues

Neutrophils are key cells of our innate immune response with essential roles for eliminating bacteria and fungi from tissues. They are also the prototype of an amoeboid migrating leukocyte. As one of the first blood-recruited immune cell types during inflammation and infection, these cells can invade almost any tissue compartment. Once in the tissue, neutrophils undergo rapid shape changes and migrate at speeds higher than most other immune cells. They move in a substrate-independent manner in interstitial spaces and do not follow predetermined tissue paths. Instead, neutrophil navigation is largely shaped by the chemokine and chemoattractant milieu around them. This highlights the decisive role of attractant-sensing G-protein coupled receptors (GPCRs) and downstream molecular pathways for controlling amoeboid neutrophil movement in tissues. A diverse repertoire of cell-surface expressed GPCRs makes neutrophils the perfect sentinel cell type to sense and detect danger-associated signals released from wounds, inflamed interstitium, dying cells, complement factors or directly from tissue-invading microbes. Moreover, neutrophils release attractants themselves, which allows communication and coordination between individual cells of a neutrophil population. GPCR-mediated positive feedback mechanisms were shown to underlie neutrophil swarming, a population response that amplifies the recruitment of amoeboid migrating neutrophils to sites of tissue injury and infection. Here we discuss recent findings and current concepts that counteract excessive neutrophil accumulation and swarm formation. In particular, we will focus on negative feedback control mechanisms that terminate neutrophil swarming to maintain the delicate balance between tissue surveillance, host protection and tissue destruction.
Increasing Fruit Weight by Editing a Cis-Regulatory Element in Tomato KLUH Promoter Using CRISPR/Cas9

CRISPR/Cas-mediated genome editing is a powerful approach to accelerate yield enhancement to feed growing populations. Most applications focus on “negative regulators” by targeting coding regions and promoters to create nulls or weak loss-of-function alleles. However, many agriculturally important traits are conferred by gain-of-function alleles. Therefore, creating gain-of-function alleles for “positive regulators” by CRISPR will be of great value for crop improvement. CYP78A family members are the positive regulators of organ weight and size in crops. In this study, we engineered allelic variation by editing tomato KLUH promoter around a single-nucleotide polymorphism (SNP) that is highly associated with fruit weight. The SNP was located in a conserved putative cis-regulatory element (CRE) as detected by the homology-based prediction and the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). Twenty-one mutant alleles with various insertion and deletion sizes were generated in the LA1589 background. Five mutant alleles (m2+4bp, m3+1bp, m5–1bp, m13–8bp, and m14–9bp) showed a consistent increase in fruit weight and a significant decrease in the proportion of small fruits in all experimental evaluations. Notably, m2+4bp and m3+1bp homozygote significantly increase fruit weight by 10.7–15.7 and 8.7–16.3%, respectively. Further analysis of fruit weight based on fruit position on the inflorescence indicated that the five beneficial alleles increase the weight of all fruits along inflorescence. We also found that allele types and transcriptional changes of SlKLUH were poor predictors of the changes in fruit weight. This study not only provides a way of identifying conserved CRE but also highlights enormous potential for CRISPR/Cas-mediated cis-engineering of CYP78A members in yield improvement.
Contact-Dependent Granzyme B-Mediated Cytotoxicity of Th17-Polarized Cells Toward Human Oligodendrocytes

Multiple sclerosis (MS) is characterized by the loss of myelin and of myelin-producing oligodendrocytes (OLs) in the central nervous system (CNS). Pro-inflammatory CD4+ Th17 cells are considered pathogenic in MS and are harmful to OLs. We investigated the mechanisms driving human CD4+ T cell-mediated OL cell death. Using fluorescent and brightfield in vitro live imaging, we found that compared to Th2-polarized cells, Th17-polarized cells show greater interactions with primary human OLs and human oligodendrocytic cell line MO3.13, displaying longer duration of contact, lower mean speed, and higher rate of vesicle-like structure formation at the sites of contact. Using single-cell RNA sequencing, we assessed the transcriptomic profile of primary human OLs and Th17-polarized cells in direct contact or separated by an insert. We showed that upon close interaction, OLs upregulate the expression of mRNA coding for chemokines and antioxidant/anti-apoptotic molecules, while Th17-polarized cells upregulate the expression of mRNA coding for chemokines and pro-inflammatory cytokines such as IL-17A, IFN-γ, and granzyme B. We found that secretion of CCL3, CXCL10, IFN-γ, TNFα, and granzyme B is induced upon direct contact in cocultures of human Th17-polarized cells with human OLs. In addition, we validated by flow cytometry and immunofluorescence that granzyme B levels are upregulated in Th17-polarized compared to Th2-polarized cells and are even higher in Th17-polarized cells upon direct contact with OLs or MO3.13 cells compared to Th17-polarized cells separated from OLs by an insert. Moreover, granzyme B is detected in OLs and MO3.13 cells following direct contact with Th17-polarized cells, suggesting the release of granzyme B from Th17-polarized cells into OLs/MO3.13 cells. To confirm granzyme B–mediated cytotoxicity toward OLs, we showed that recombinant human granzyme B can induce OLs and MO3.13 cell death. Furthermore, pretreatment of Th17-polarized cells with a reversible granzyme B blocker (Ac-IEPD-CHO) or a natural granzyme B blocker (serpina3N) improved survival of MO3.13 cells upon coculture with Th17 cells. In conclusion, we showed that human Th17-polarized cells form biologically significant contacts with human OLs and exert direct toxicity by releasing granzyme B.
Interoception Dysfunction Contributes to the Negative Emotional Bias in Major Depressive Disorder

Background Previous research studies have demonstrated that impaired interoception is involved in emotional information processing in major depressive disorder (MDD). Heartbeat-evoked potential (HEP) amplitudes, an index for interoception, could be manipulated by emotional faces in healthy people. Considering negative emotional bias is the core characteristic in MDD, we hypothesized that interoception dysfunction was associated with the negative emotional bias in MDD. Methods An electroencephalogram (EEG) study under an emotional faces task was applied to explore the relationship between interoception and emotional bias. HEPs before emotional faces stimuli were used to predict the late positive potential (LPP) amplitudes and it worked as an index of emotional bias. Twenty-seven patients with MDD and 27 healthy controls (HCs) participated in this study. Source analysis gave an auxiliary description for results in sensory level. Results Major depressive disorders (MDDs) had poor performance in the heartbeat count task (HCT) and attenuate HEP average amplitudes (455–550 ms). Compared with HCs, cluster-based permutation t-tests revealed that MDDs had attenuated LPP amplitudes (300–1,000 ms) over centroparietal regions and enhanced LPP amplitudes over frontocentral regions. Furthermore, abnormal attenuated HEPs could predict aberrant LPPs under sad face stimuli in MDDs, which could be associated with the dysfunction of the anterior cingulate cortex (ACC) and right insula. Conclusion Mediated by ACC and insula, interoception dysfunction contributes to the negative emotional bias of MDD, highlighting the importance of interoception in the disorder.
Identification of Veratrum Species in Pimacao Based on ITS2 Sequences and Steroidal Alkaloids by a Pseudo-Targeted Metabolomics Method

Pimacao is a traditional Chinese folk medicine and is the main component of the famous Chinese herbal remedy “Yunnan Baiyao” for its significant analgesic activity in the treatment of wounds. Due to increases in consumption, its wild population is now difficult to find, and adulterant from the same genus has occurred. However, this is challenging to distinguish the species of Veratrum in Pimacao using dried roots and rhizomes or medicinal powder. ITS2 sequences and steroidal alkaloids by the non-targeted and pseudo-targeted metabolomics methods were taken advantage of establishing an effective identification method. Based on the ITS2 sequence, metabolite profiling of steroidal alkaloids and morphological characteristics, the classification of two distinct subspecies in V. mengzeanum has been reinforced. In addition, the new subspecies V. mengzeanum subsp. phuwae was collected in China for the first time. The ITS2 sequence could be used in the identification of V. taliense, V. mengtzeanum, V. stenophyllum, and V. nigrum, but is insufficient for intraspecific identification. Simultaneously, 147 variables were labeled by non-targeted analysis accomplished utilizing an ultra-high-performance liquid chromatography electrospray ionization orbitrap tandem mass spectrometry (UPLC-ESI-QE-Orbitrap-MS) system consisting of an Orbitrap QE HF-X. Followed by a pseudo-targeted analysis method developed for the Qtrap 6500-plus mass spectrometry system coupled with an ESI source, 29 labeled steroidal alkaloids detected by the MRM mode could distinguish between four species. Notably, 25 labeled steroidal alkaloids could distinguish between three closely related species. These have the potential to be used as markers for identification. Furthermore, there were several variables with statistical differences between two subspecies of V. mengtzeanum and populations of V. taliense, V. mengtzeanum, and V. stenophyllum.
Recent Evolution of Glaciers in the Manaslu Region of Nepal From Satellite Imagery and UAV Data (1970–2019)

Glacierized mountain ranges such as the Himalaya comprise a variety of glacier types, including clean and debris-covered glaciers. Monitoring their behaviour over time requires an assessment of changes in area and elevation along with surface features and geomorphology. In this paper we quantify the surface evolution of glacier systems in the Manaslu region of Nepal over the last five decades using 2013/2019 multi-sensor imagery and elevation data constructed from 1970 declassified Corona imagery and 1970 declassified Corona imagery. We investigate area changes, glacier thickness, geodetic glacier mass balance and surface velocity changes at regional scales and focus on the Ponkar Glacier and Thulagi Glacier and Lake for an in-depth assessment of surface geomorphology and surface feature dynamics (ponds, vegetation and ice cliffs). The time series of surface elevation changes for the lower ablation area of Ponkar Glacier is extended using 2019 UAV-based imagery and field-based ablation rates measured over the period 2016–2019. Glaciers in the Manaslu region experienced a mean area loss of −0.26 ± 0.0001% a−1 between 1970 and 2019. The mean surface lowering was −0.20 ± 0.02 ma−1 over the period 1970 to 2013, corresponding to a regional geodetic mass balance of −0.17 ± 0.03 m w. e.a−1. Overall, debris-covered glaciers had slightly higher thinning rates compared to clean ice glaciers; lake-terminating glaciers had double thinning rates compared to land-terminating glaciers. Individual glacier mass balance was negatively controlled by glacier slope and mean glacier elevation. During the period 1970 to 2013, Ponkar Glacier had a geodetic mass balance of −0.06 ± 0.01 m w. e.a−1, inversely correlated with parts of the central trunk thickening. Between 2013 and 2019 there was a nine-fold increase in the thinning rates over the lower parts of the glacier tongue relative to the period 1970–2013. Ice-surface morphology changes between 1970 and 2019 on Ponkar Glacier include a decrease in ogives and open crevasses, an increase in ice cliffs and ponds and the expansion of the supraglacial debris and ice-surface vegetation. These changes point to reduced ice-dynamic activity and are commensurate with the observed recession and negative glacier mass balance over the last five decades.
Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery Disease

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and the main leading cause of morbidity and mortality worldwide, posing a huge socio-economic burden to the society and health systems. Therefore, timely and precise identification of people at high risk of CAD is urgently required. Most current CAD risk prediction approaches are based on a small number of traditional risk factors (age, sex, diabetes, LDL and HDL cholesterol, smoking, systolic blood pressure) and are incompletely predictive across all patient groups, as CAD is a multi-factorial disease with complex etiology, considered to be driven by both genetic, as well as numerous environmental/lifestyle factors. Diet is one of the modifiable factors for improving lifestyle and disease prevention. However, the current rise in obesity, type 2 diabetes (T2D) and CVD/CAD indicates that the “one-size-fits-all” approach may not be efficient, due to significant variation in inter-individual responses. Recently, the gut microbiome has emerged as a potential and previously under-explored contributor to these variations. Hence, efficient integration of dietary and gut microbiome information alongside with genetic variations and clinical data holds a great promise to improve CAD risk prediction. Nevertheless, the highly complex nature of meals combined with the huge inter-individual variability of the gut microbiome poses several Big Data analytics challenges in modeling diet-gut microbiota interactions and integrating these within CAD risk prediction approaches for the development of personalized decision support systems (DSS). In this regard, the recent re-emergence of Artificial Intelligence (AI) / Machine Learning (ML) is opening intriguing perspectives, as these approaches are able to capture large and complex matrices of data, incorporating their interactions and identifying both linear and non-linear relationships. In this Mini-Review, we consider (1) the most used AI/ML approaches and their different use cases for CAD risk prediction (2) modeling of the content, choice and impact of dietary factors on CAD risk; (3) classification of individuals by their gut microbiome composition into CAD cases vs. controls and (4) modeling of the diet-gut microbiome interactions and their impact on CAD risk. Finally, we provide an outlook for putting it all together for improved CAD risk predictions.
Progresses and Prospects of Neuroprotective Agents-Loaded Nanoparticles and Biomimetic Material in Ischemic Stroke

Ischemic stroke remains the leading cause of death and disability, while the main mechanisms of dominant neurological damage in stroke contain excitotoxicity, oxidative stress, and inflammation. The clinical application of many neuroprotective agents is limited mainly due to their inability to cross the blood-brain barrier (BBB), short half-life and low bioavailability. These disadvantages can be better eliminated/reduced by nanoparticle as the carrier of these drugs. This review expounded the currently hot researched nanomedicines from the perspective of the mechanism of ischemic stroke. In addition, this review describes the bionic nanomedicine delivery strategies containing cells, cell membrane vesicles and exosomes that can effectively avoid the risk of clearance by the reticuloendothelial system. The potential challenges and application prospect for clinical translation of these delivery platforms were also discussed.
Hot Tea Consumption and Esophageal Cancer Risk: A Meta-Analysis of Observational Studies

Objective Many laboratory studies have shown that tea consumption protected against the development of esophageal cancer (EC). However, in epidemiological studies, inconsistent or even contradictory results were frequently observed, especially when drinking tea at higher temperatures. Methods We conducted a meta-analysis based on published observational studies to explore whether hot tea consumption was a risk factor of EC. Relevant studies were searched in PubMed, Embase, and Web of science up to October 13, 2021, and we also manually retrieved the literature in the included studies and recent reviews. Results A total of 23 eligible reports were identified, including 5,050 cases and 10,609 controls, and a meta-analysis with Comprehensive Meta-Analysis (CMA) software (version 2.0) was conducted. A statistically significant increased EC risk was observed when drinking tea at higher temperature (odds ratios (ORs) = 1.79, 95% CI: 1.48–2.15, p = 0.00). Except for esophageal adenocarcinoma (EAC), this increased risk was also found in the majority of subgroups, which are the European and Australian populations. Conclusions This meta-analysis showed that people who drank hot tea had a significantly increased risk of Esophageal squamous cell carcinoma (ESCC), but no significant association for EAC.
From Mouth to Brain: Distinct Supragingival Plaque Microbiota Composition in Cerebral Palsy Children With Caries

Children with cerebral palsy (CP) present a higher prevalence and severity of caries. Although researchers have studied multiple risk factors for caries in CP, the role of microorganisms in caries remains one of the critical factors worth exploring. In order to explore the differences in the supragingival plaque microbiota (SPM), supragingival plaque samples were collected from 55 CP children and 23 non-CP children for 16S rRNA sequencing. Distinct SPM composition was found between CP children with severe caries (CPCS) and non-CP children with severe caries (NCPCS). Further subanalysis was also done to identify if there were any differences in SPM among CP children with different degrees of caries, namely, caries-free (CPCF), mild to moderate caries (CPCM), and severe caries (CPCS). After selecting the top 15 most abundant species in all groups, we found that CPCS was significantly enriched for Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, Porphyromonas endodontalis, Catonella morbi, Alloprevotella tannerae, Parvimonas micra, Streptobacillus moniliformis, and Porphyromonas canoris compared to NCPCS. By comparing CPCF, CPCM, and CPCS, we found that the core caries-associated microbiota in CP children included Prevotella, Alloprevotella, Actinomyces, Catonella, and Streptobacillus, while Capnocytophaga and Campylobacter were dental health-associated microbiota in CP children. Alpha diversity analysis showed no significant difference between NCPCS and CPCS, but the latter had a much simpler core correlation network than that of NCPCS. Among CP children, CPCM and CPCF displayed lower bacterial diversity and simpler correlation networks than those of CPCS. In summary, the study showed the specific SPM characteristics of CPCS compared to NCPCS and revealed the core SPM in CP children with different severities of caries (CPCF, CPCM, and CPCS) and their correlation network. Hopefully, the study would shed light on better caries prevention and therapies for CP children. Findings from the current study offer exciting insights that warrant larger cohort studies inclusive of saliva and feces samples to investigate the potential pathogenic role of oral microbiota through the oral–gut–brain axis in CP children with caries.