Quantum spin driven Yu-Shiba-Rusinov multiplets and fermion-parity-preserving phase transition in K3C60.

Magnetic impurities in superconductors are of increasing interest due to emergent Yu-Shiba-Rusinov (YSR) states and Majorana zero modes for fault-tolerant quantum computation. However, a direct relationship between the YSR multiple states and magnetic anisotropy splitting of quantum impurity spins remains poorly characterized. By using scanning tunneling microscopy, we systematically resolve individual transition-metal (Fe, Cr, and Ni) impurities induced YSR multiplets as well as their Zeeman effects in the K3C60 superconductor. The YSR multiplets show identical d orbital-like wave functions that are symmetry-mismatched to the threefold K3C60(1 1 1) host surface, breaking point-group symmetries of the spatial distribution of YSR bound states in real space. Remarkably, we identify an unprecedented fermion-parity-preserving quantum phase transition between ground states with opposite signs of the uniaxial magnetic anisotropy that can be manipulated by an external magnetic field. These findings can be readily understood in terms of anisotropy splitting of quantum impurity spins, and thus elucidate the intricate interplay between the magnetic anisotropy and YSR multiplets.

3D reconstruction of the mouse cochlea from scRNA-seq data suggests morphogen-based principles in apex-to-base specification.

In the mammalian auditory system, frequency discrimination depends on numerous morphological and physiological properties of the organ of Corti, which gradually change along the apex-to-base (tonotopic) axis of the organ. For example, the basilar membrane stiffness changes tonotopically, thus affecting the tuning properties of individual hair cells. At the molecular level, those frequency-specific characteristics are mirrored by gene expression gradients; however, the molecular mechanisms controlling tonotopic gene expression in the mouse cochlea remain elusive. Through analyzing single-cell RNA sequencing (scRNA-seq) data from E12.5 and E14.5 time points, we predicted that morphogens, rather than a cell division-associated mechanism, confer spatial identity in the extending cochlea. Subsequently, we reconstructed the developing cochlea in 3D space from scRNA-seq data to investigate the molecular pathways mediating positional information. The retinoic acid (RA) and hedgehog pathways were found to form opposing apex-to-base gradients, and functional interrogation using mouse cochlear explants suggested that both pathways jointly specify the longitudinal axis.

Bergapten exerts a chondroprotective effect in temporomandibular joint osteoarthritis by combining intestinal flora alteration and reactive oxygen species reduction.

Bergapten, a furanocoumarin naturally occurring in bergamot essential oil, has been demonstrated to have the potential to alleviate osteoarthritis-related symptoms via its anti-inflammatory activity. Although its systemic bioavailability is limited, its precise mechanisms of action and effects on temporomandibular joint osteoarthritis (TMJOA) and its relationship with the intestinal flora remain unclear. Here, we explored the anti-TMJOA effect of BGT combined with the interleukin-1ß-induced inflammatory response of chondrocytes in a monosodium iodoacetate (MIA)-induced TMJOA rat model. It was confirmed that BGT effectively reduced proinflammatory mediators and increased type II collagen, bone volume, and trabecular number of condyles in TMJOA rats. Importantly, the oral administration of BGT altered the intestinal flora of rats by increasing the relative abundances of nine prebiotic species and decreasing the relative abundance of one potential species. In addition, BGT considerably reduced reactive oxygen species (ROS) levels by suppressing glutathione, oxidized glutathione, and superoxide dismutase in the serum and malondialdehyde in urine. These results suggest that BGT exerts a chondroprotective effect, most likely by improving the intestinal flora and reducing ROS production associated with TMJOA in rats. This finding indicates a novel beneficial effect of BGT on the prevention and treatment of TMJOA.

Quantification of pharyngeal airway space changes after two-jaw orthognathic surgery in skeletal class III patients.

BACKGROUND: Skeletal class III malocclusion is a common dentofacial deformity. Orthognathic treatment changes the position of the jaws and affects the shape of the upper airway to some extent. The aim of this study was to use multislice spiral computer tomography data and orthognathic knowledge to quantify the relationship between the amount of surgical movement of the maxilla or mandible in all three spatial planes and the changes in airway volume that occurred. METHODS: A retrospective study of 50 patients was conducted. Preoperative and postoperative linear changes related to skeletal movements of the maxilla and mandible were measured and compared to changes in the most constricted axial level (MCA) and its anteroposterior (MCA-AP) and transverse diameters (MCA-TV). Correlation tests and linear regression analysis were performed. RESULTS: Significant interactions were observed between the anterior vertical movement of the maxilla and the MCA-AP. The anteroposterior movement distance of the mandible was significantly correlated with changes in the oropharyngeal, velopharyngeal, total airway volume, MCA, MCA-AP, and MCA-TV. The change in the mandibular plane angle was significantly correlated with the change in velopharyngeal volume, total airway volume (nasopharynx, oropharynx, velopharynx), and MCA. The linear regression model showed that oropharyngeal volume decreased by 350.04 mm3, velopharyngeal volume decreased by 311.50 mm3, total airway volume decreased by 790.46 mm3, MCA decreased by 10.96 mm2 and MCA-AP decreased by 0.73 mm2 when point B was setback by 1 mm. CONCLUSIONS: Anteroposterior mandibular control is the key to successful airway management in all patients. This study provides estimates of volume change per millimeter of setback to guide surgeons in treatment planning.

The effect of GelMA/alginate interpenetrating polymeric network hydrogel on the performance of porous zirconia matrix for bone regeneration applications.

Bone tissue is a natural composite, exhibiting complicated structures and unique mechanical/biological properties. With an attempt of mimicking the bone tissue, a novel inorganic-organic composite scaffolds (ZrO2-GM/SA) was designed and prepared via the vacuum infiltration method and the single/double cross-linking strategy by blending GelMA/alginate (GelMA/SA) interpenetrating polymeric network (IPN) into the porous zirconia (ZrO2) scaffold. The structure, morphology, compressive strength, surface/interface properties, and biocompatibility of the ZrO2-GM/SA composite scaffolds were characterized to evaluate the performance of the composite scaffolds. Results showed that compared to ZrO2 bare scaffolds with well-defined open pores, the composite scaffolds prepared by double cross-linking of GelMA hydrogel and sodium alginate (SA) presented a continuous, tunable and honeycomb-like microstructure. Meanwhile, GelMA/SA showed favorable and controllable water-uptake capacity, swelling property and degradability. After the introduction of IPN components, the mechanical strength of composite scaffolds was further improved. The compressive modulus of composite scaffolds was significantly higher than the bare ZrO2 scaffolds. In addition, ZrO2-GM/SA composite scaffolds had highly biocompatibility and displayed a potent proliferation and osteogenesis of MC3T3-E1 pre-osteoblasts compared to bare ZrO2 scaffolds and ZrO2-GelMA composite scaffolds. At the same time, ZrO2-10GM/1SA composite scaffold regenerated significantly greater bone than other groups in vivo. This study demonstrated that the proposed ZrO2-GM/SA composite scaffolds had great research and application potential in bone tissue engineering.

Hydrogels for Treatment of Different Degrees of Osteoarthritis.

Osteoarthritis (OA) is a common disease that severely restricts human activities and degrades the quality of life. Every year, millions of people worldwide are diagnosed with osteoarthritis, placing a heavy burden on society. Hydrogels, a polymeric material with good biocompatibility and biodegradability, are a novel approach for the treatment of osteoarthritis. In recent years, this approach has been widely studied with the development of materials science and tissue engineering technology. We reviewed the research progress of hydrogels in the treatment of osteoarthritis in the past 3 years. We summarized the required hydrogel properties and current applications according to the development and treatment of osteoarthritis. Furthermore, we listed the challenges of hydrogels for different types of osteoarthritis and presented prospects for future development.

Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data.

BACKGROUND: Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks. RESULTS: The top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs. CONCLUSIONS: Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.

Semiconductor-Metal Phase Transition and Emergent Charge Density Waves in 1T-ZrX2 (X = Se, Te) at the Two-Dimensional Limit.

A charge density wave (CDW) is a collective quantum phenomenon in metals and features a wavelike modulation of the conduction electron density. A microscopic understanding and experimental control of this many-body electronic state in atomically thin materials remain hot topics in materials physics. By means of material engineering, we realized a dimensionality and Zr intercalation induced semiconductor-metal phase transition in 1T-ZrX2 (X = Se, Te) ultrathin films, accompanied by a commensurate 2 × 2 CDW order. Furthermore, we observed a CDW energy gap of up to 22 meV around the Fermi level. Fourier-transformed scanning tunneling microscopy and angle-resolved photoemission spectroscopy reveal that 1T-ZrX2 films exhibit the simplest Fermi surface among the known CDW materials in TMDCs, consisting only of a Zr 4d derived elliptical electron conduction band at the corners of the Brillouin zone.

Automatic detection of anteriorly displaced temporomandibular joint discs on magnetic resonance images using a deep learning algorithm.

OBJECTIVES: This study aimed to develop models that can automatically detect anterior disc displacement (ADD) of the temporomandibular joint (TMJ) on MRIs before orthodontic treatment to reduce the risk of developing serious complications after treatment. METHODS: We used 9009 sagittal MRI of the TMJ as input and constructed three sets of deep learning models to detect ADD automatically. Deep learning models were developed using a convolutional neural network (CNN) based on the ResNet architecture and the "Imagenet" database. Five-fold cross-validation, oversampling, and data augmentation techniques were applied to reduce the risk of overfitting the model. The accuracy and area under the curve (AUC) of the three models were compared. RESULTS: The performance of the maximum open mouth position model was excellent with accuracy and AUC of 0.970 (±0.007) and 0.990 (±0.005), respectively. For closed mouth position models, the accuracy and AUC of diagnostic Criteria 1 were 0.863 (±0.008) and 0.922 (±0.009), respectively significantly higher than that of diagnostic Criteria 2 with 0.839 (±0.013) (p = 0.009) and AUC of 0.885 (±0.018) (p = 0.003). The classification activation heat map also improved our understanding of the models and visually displayed the areas that play a key role in the model recognition process. CONCLUSION: Our CNN model resulted in high accuracy and AUC in detecting ADD and can therefore potentially be used by clinicians to assess ADD before orthodontic treatment, and hence improve treatment outcomes.

A novel method for clinical risk prediction with low-quality data.

In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital readmission, and chronic disease onset) are constantly struggling with low-quality issues, namely redundant and highly correlated features, extreme category imbalances, and most importantly, a large number of missing values. In most existing work, each patient is represented as a value vector with the fixed-length from some feature space, and missing values are forced to be imputed, which introduces much noise for prediction if the data set is highly incomplete. Besides, other challenges are either remaining unresolved or only partially solved when modeling, but without a systematic approach. In this paper, we propose a novel framework to address these low-quality problems, that we first treat patients as bags with the various number of feature-value pairs, called instances, and map them to an embedding space through our proposed feature embedding method to learn from it directly. In this way, predictive models can avoid the negative impact of missing data naturally. A novel multi-instance neural network is then connected, using two computational modules to deal with the problems of correlated and redundant features: multi-head attention and attention-based multi-instance pooling. They are capable of capturing the instance correlations and locating valuable information in each instance or bag. The feature embedding and multi-instance neural network are parameterized and optimized jointly in an end-to-end manner. Moreover, the training process is under both main and auxiliary supervision with focal loss functions to avoid the caveat of a highly imbalanced label set. This proposed framework is named AMI-Net3. We evaluate it on three suitable data sets from real-world settings with different clinical risk prediction tasks: adverse drug reaction of risperidone, schizophrenia relapse, and invasive fungi infection, respectively. The comprehensive experimental results demonstrate the effectiveness and superiority of our proposed method over competitive baselines.

Mapping the regulatory landscape of auditory hair cells from single-cell multi-omics data.

Auditory hair cells transduce sound to the brain, and in mammals, these cells reside together with supporting cells in the sensory epithelium of the cochlea, called the organ of Corti. To establish the organ's delicate function during development and differentiation, spatiotemporal gene expression is strictly controlled by chromatin accessibility and cell type-specific transcription factors, jointly representing the regulatory landscape. Bulk sequencing technology and cellular heterogeneity obscured investigations on the interplay between transcription factors and chromatin accessibility in inner ear development. To study the formation of the regulatory landscape in hair cells, we collected single-cell chromatin accessibility profiles accompanied by single-cell RNA data from genetically labeled murine hair cells and supporting cells after birth. Using an integrative approach, we predicted cell type-specific activating and repressing functions of developmental transcription factors. Furthermore, by integrating gene expression and chromatin accessibility data sets, we reconstructed gene regulatory networks. Then, using a comparative approach, 20 hair cell-specific activators and repressors, including putative downstream target genes, were identified. Clustering of target genes resolved groups of related transcription factors and was used to infer their developmental functions. Finally, the heterogeneity in the single-cell data allowed us to spatially reconstruct transcriptional as well as chromatin accessibility trajectories, indicating that gradual changes in the chromatin accessibility landscape are lagging behind the transcriptional identity of hair cells along the organ's longitudinal axis. Overall, this study provides a strategy to spatially reconstruct the formation of a lineage-specific regulatory landscape using a single-cell multi-omics approach.

Direct Visualization of Ambipolar Mott Transition in Cuprate CuO_{2} Planes.

Identifying the essence of doped Mott insulators is one of the major outstanding problems in condensed matter physics and the key to understanding the high-temperature superconductivity in cuprates. We report real space visualization of Mott insulator-metal transition in Sr_{1-x}La_{x}CuO_{2+y} cuprate films that cover both the electron- and hole-doped regimes. Tunneling conductance measurements directly on the copper-oxide (CuO_{2}) planes reveal a systematic shift in the Fermi level, while the fundamental Mott-Hubbard band structure remains unchanged. This is further demonstrated by exploring the atomic-scale electronic response of CuO_{2} to substitutional dopants and intrinsic defects in a sister compound Sr_{0.92}Nd_{0.08}CuO_{2}. The results may be better explained in the framework of self-modulation doping, similar to that in semiconductor heterostructures, and form a basis for developing any microscopic theories for cuprate superconductivity.

Direct Observation of Full-Gap Superconductivity and Pseudogap in Two-Dimensional Fullerides.

Alkali-fulleride superconductors with a maximum critical temperature T_{c}∼40 K exhibit a similar electronic phase diagram to that of unconventional high-T_{c} superconductors. Here we employ cryogenic scanning tunneling microscopy to show that trilayer K_{3}C_{60} displays fully gapped strong coupling s-wave superconductivity, accompanied by a pseudogap above T_{c}∼22 K and within vortices. A precise control of the electronic correlations and potassium doping enables us to reveal that superconductivity occurs near a superconductor-Mott-insulator transition and reaches maximum at half-filling. The s-wave symmetry retains over the entire phase diagram, which, in conjunction with an abrupt decline of the superconductivity below half-filling, indicates that alkali fullerides are predominantly phonon-mediated superconductors, although the electronic correlations also come into play.

Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions.

Gene set enrichment (GSE) testing enhances the biological interpretation of ChIP-seq data and other large sets of genomic regions. Our group has previously introduced two GSE methods for genomic regions: ChIP-Enrich for narrow regions and Broad-Enrich for broad regions. Here, we introduce Poly-Enrich, which has wider applicability, additional capabilities and models the number of peaks assigned to a gene using a generalized additive model with a negative binomial family to determine gene set enrichment, while adjusting for gene locus length. As opposed to ChIP-Enrich, Poly-Enrich works well even when nearly all genes have a peak, illustrated by using Poly-Enrich to characterize pathways and types of genic regions enriched with different families of repetitive elements. By comparing Poly-Enrich and ChIP-Enrich results with ENCODE ChIP-seq data, we found that the optimal test depends more on the pathway being regulated than on properties of the transcription factors. Using known transcription factor functions, we discovered clusters of related biological processes consistently better modeled with Poly-Enrich. This suggests that the regulation of certain processes may be modified by multiple binding events, better modeled by a count-based method. Our new hybrid method automatically uses the optimal method for each gene set, with correct FDR-adjustment.

Effects of inferior alveolar nerve rupture on bone remodeling of the mandible: A preliminary study.

Although various animal studies have indicated that sensory nerves played an important role in bone metabolism and nerve injury could impair the process of bone remodeling, the actual effect of sensory nerve rupture on human bones remains unclear. The aim of this preliminary study was to investigate the effect of inferior alveolar nerve (IAN) rupture on mandibular bone remodeling of patients underwent bilateral sagittal split ramus osteotomy (BSSRO).Ten patients with unilateral IAN rupture during BSSRO were involved in this study. Neurosensory examinations were employed to assess the sensory function of bilateral IAN. The remodeling process of the post-operational mandible was evaluated by panoramic radiographs and computed tomography (CT) scans.Neurosensory examinations indicated that nerve rupture resulted in significant hypoesthesia at the IAN-rupture side. Assessment of panoramic radiographs showed no evident alterations of bone structure at the IAN-rupture side of mandible. Evaluation of CT images also indicated no statistical difference in bone density and thickness between IAN-rupture side and contralateral side.Accordingly, our study indicated that IAN rupture may not significantly impair the short-term bone remodeling process of human mandible.

Incidence of Pneumothorax Experienced After Orthognathic Surgery.

The purpose of this study is to evaluate the frequency of pneumothorax following orthognathic surgery and describe its clinical presentation. A retrospective analysis of a hospital database was carried out on consecutive patients with normal presurgical clinical assessment, laboratory findings, and chest X-ray who underwent orthognathic surgery from January 2007 to September 2018 in the Department of Oral and Craniomaxillofacial Surgery, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. Two patients (0.038%), 1 male (age 20 years) and 1 female (age 32 years), complained of respiratory difficulty and chest pain and were clearly diagnosed with postoperative pneumothorax by radiographic chest X-rays from a sample of 5229 consecutive patients during the study period. Intercostal drainage under local anesthesia was performed immediately and the treatment effects for both patients were satisfactory. The present study findings indicate that although orthognathic surgeries can be safely performed in patients with craniofacial anomalies, some unexpected complications such as pneumothorax may occur. Therefore, accurate postoperative follow-up must be done in every patient to monitor possible clinical complications. Patients who experience respiratory difficulty and postoperative chest pain may have pneumothorax, and once it is diagnosed, treatment should be promptly carried out to eliminate further severe sequelae.

Value of reduced glomerular filtration rate assessment with cardiometabolic index: insights from a population-based Chinese cohort.

BACKGROUND: Recent studies have suggested that cardiometabolic index (CMI), a novel estimate of visceral adipose tissue, could be of use in the evaluation of cardiovascular risk factors. However, the potential utility and clinical significance of CMI in the detection of reduced estimated glomerular filtration rate (eGFR) remains uncertain. The purpose of this study was to investigate the usefulness of CMI in assessing reduced eGFR in the general Chinese population. METHODS: This cross-sectional analysis included 11,578 participants (mean age: 53.8 years, 53.7% females) from Northeast China Rural Cardiovascular Health Study (NCRCHS) of general Chinese population (data collected from January 2013 to August 2013). CMI was calculated by triglyceride to high density lipoprotein cholesterol ratio multiply waist-to-height ratio. Reduced eGFR was defined as eGFR< 60 ml/min per 1.73m2. Multivariate regressions were performed to determine CMI's association with eGFR value and eGFR reduction, ROC analyses were employed to investigate CMI's discriminating ability for decreased eGFR. RESULTS: The prevalence of reduced eGFR was 1.7% in males and 2.5% in females. CMI was notably more adverse in reduced eGFR groups, regardless of genders. In fully adjusted multivariate linear models, each 1 SD increment of CMI caused 3.150 ml/min per 1.73m2 and 2.411 ml/min per 1.73m2 loss of eGFR before CMI reached 1.210 and 1.520 in males and females, respectively. In logistic regression analyses, per 1 SD increase of CMI brought 51.6% additional risk of reduced eGFR in males while caused 1.347 times of risk in females. After divided into quartiles, people in the top quartile of CMI had higher adjusted ORs of having reduced eGFR, with ORs of 4.227 (1.681, 10.627) and 3.442 (1.685-7.031) for males and females respectively. AUC of CMI was revealed to be 0.633 (0.620-0.646) in males and 0.684 (0.672-0.695) in females. CONCLUSIONS: Higher CMI was independently associated with greater burden of reduced eGFR, highlighting VAT distribution and dysfunction as a potential mechanism underlying the association of obesity with kidney damage and adverse cardiovascular outcomes. The findings from this study provided important insights regarding the potential usefulness and clinical relevance of CMI in the detection of reduced eGFR among general Chinese population.