All-Optical Reconfigurable Excitonic Charge States in Monolayer MoS2.

Excitons are quasi-particles composed of electron-hole pairs through Coulomb interaction. Due to the atomic-thin thickness, they are tightly bound in monolayer transition metal dichalcogenides (TMDs) and dominate their optical properties. The capability to manipulate the excitonic behavior can significantly influence the photon emission or carrier transport performance of TMD-based devices. However, on-demand and region-selective manipulation of the excitonic states in a reversible manner remains challenging so far. Herein, harnessing the coordinated effect of femtosecond-laser-driven atomic defect generation, interfacial electron transfer, and surface molecular desorption/adsorption, we develop an all-optical approach to manipulate the charge states of excitons in monolayer molybdenum disulfide (MoS2). Through steering the laser beam, we demonstrate reconfigurable optical encoding of the excitonic charge states (between neutral and negative states) on a single MoS2 flake. Our technique can be extended to other TMDs materials, which will guide the design of all-optical and reconfigurable TMD-based optoelectronic and nanophotonic devices.

Preclinical validation of a novel deep learning-based metal artifact correction algorithm for orthopedic CT imaging.

PURPOSE: To validate a novel deep learning-based metal artifact correction (MAC) algorithm for CT, namely, AI-MAC, in preclinical setting with comparison to conventional MAC and virtual monochromatic imaging (VMI) technique. MATERIALS AND METHODS: An experimental phantom was designed by consecutively inserting two sets of pedicle screws (size Φ 6.5 × 30-mm and Φ 7.5 × 40-mm) into a vertebral specimen to simulate the clinical scenario of metal implantation. The resulting MAC, VMI, and AI-MAC images were compared with respect to the metal-free reference image by subjective scoring, as well as by CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and correction accuracy via adaptive segmentation of the paraspinal muscle and vertebral body. RESULTS: The AI-MAC and VMI images showed significantly higher subjective scores than the MAC image (all p < 0.05). The SNRs and CNRs on the AI-MAC image were comparable to the reference (all p > 0.05), whereas those on the VMI were significantly lower (all p < 0.05). The paraspinal muscle segmented on the AI-MAC image was 4.6% and 5.1% more complete to the VMI and MAC images for the Φ 6.5 × 30-mm screws, and 5.0% and 5.1% for the Φ 7.5 × 40-mm screws, respectively. The vertebral body segmented on the VMI was closest to the reference, with only 3.2% and 7.4% overestimation for Φ 6.5 × 30-mm and Φ 7.5 × 40-mm screws, respectively. CONCLUSIONS: Using metal-free reference as the ground truth for comparison, the AI-MAC outperforms VMI in characterizing soft tissue, while VMI is useful in skeletal depiction.

Clinical validation of an AI-based motion correction reconstruction algorithm in cerebral CT.

OBJECTIVES: To evaluate the clinical performance of an artificial intelligence (AI)-based motion correction (MC) reconstruction algorithm for cerebral CT. METHODS: A total of 53 cases, where motion artifacts were found in the first scan so that an immediate rescan was taken, were retrospectively enrolled. While the rescanned images were reconstructed with a hybrid iterative reconstruction (IR) algorithm (reference group), images of the first scan were reconstructed with both the hybrid IR (motion group) and the MC algorithm (MC group). Image quality was compared in terms of standard deviation (SD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), the mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mutual information (MI), as well as subjective scores. The diagnostic performance for each case was evaluated accordingly by lesion detectability or the Alberta Stroke Program Early CT Score (ASPECTS) assessment. RESULTS: Compared with the motion group, the SNR and CNR of the MC group were significantly increased. The MSE, PSNR, SSIM, and MI with respect to the reference group were improved by 44.1%, 15.8%, 7.4%, and 18.3%, respectively (all p < 0.001). Subjective image quality indicators were scored higher for the MC than the motion group (p < 0.05). Improved lesion detectability and higher AUC (0.817 vs 0.614) in the ASPECTS assessment were found for the MC to the motion group. CONCLUSIONS: The AI-based MC reconstruction algorithm has been clinically validated for reducing motion artifacts and improving diagnostic performance of cerebral CT. KEY POINTS: • An artificial intelligence-based motion correction (MC) reconstruction algorithm has been clinically validated in both qualitative and quantitative manner. • The MC algorithm reduces motion artifacts in cerebral CT and increases the diagnostic confidence for brain lesions. • The MC algorithm can help avoiding rescans caused by motion and improving the efficiency of cerebral CT in the emergency department.

Effects of inhaled JAK inhibitor GDC-4379 on exhaled nitric oxide and peripheral biomarkers of inflammation.

BACKGROUND: Janus Kinases (JAKs) mediate activity of many asthma-relevant cytokines. GDC-0214, an inhaled small molecule JAK1 inhibitor, has previously been shown to reduce fractional exhaled nitric oxide (FeNO) in patients with mild asthma, but required an excessive number of inhalations. AIM: To assess whether GDC-4379, a new inhaled JAK inhibitor, reduces FeNO and peripheral biomarkers of inflammation. METHODS: This study assessed the activity of GDC-4379 in a double-blind, randomized, placebo-controlled, Phase 1 study in patients with mild asthma. Participants included adults (18-65y) with a diagnosis of asthma for ≥6 months, forced expiratory volume in 1 s (FEV1)> 70% predicted, FeNO >40 ppb, using as-needed short-acting beta-agonist medication only. Four sequential, 14-day, ascending-dose cohorts (10 mg QD, 30 mg QD, 40 mg BID, and 80 mg QD) of 12 participants each were randomized 2:1 to GDC-4379 or placebo. The primary activity outcome was percent change from baseline (CFB) in FeNO to Day 14 compared to the pooled placebo group. Safety, tolerability, pharmacokinetics, and pharmacodynamic biomarkers, including blood eosinophils, serum CCL17, and serum CCL18, were also assessed. RESULTS: Of 48 enrolled participants, the mean age was 25 years and 54% were female. Median (range) FeNO at baseline was 79 (41-222) ppb. GDC-4379 treatment led to dose-dependent reductions in FeNO. Compared to placebo, mean (95% CI) percent CFB in FeNO to Day 14 was: -6 (-43, 32) at 10 mg QD, -26 (-53, 2) at 30 mg QD, -55 (-78, -32) at 40 mg BID and -52 (-72, -32) at 80 mg QD. Dose-dependent reductions in blood eosinophils and serum CCL17 were also observed. Higher plasma drug concentrations corresponded with greater FeNO reductions. No serious AEs occurred. The majority of AEs were mild to moderate. The most common AEs were headache and oropharyngeal pain. Minor changes in neutrophils were noted at 80 mg QD, but were not considered clinically meaningful. CONCLUSIONS: In patients with mild asthma, 14-day treatment with GDC-4379 reduced FeNO levels and peripheral biomarkers of inflammation. Treatment was well tolerated without any major safety concerns. AUSTRALIAN NEW ZEALAND CLINICAL TRIALS REGISTRY: ACTRN12619000227190.

Improving coverage probabilities for parametric tolerance intervals via bootstrap calibration.

Statistical tolerance intervals are commonly employed in biomedical and pharmaceutical research, such as in lifetime analysis, the assessment of biosimilarity of branded and generic versions of biopharmaceutical drugs, and in quality control of drug products to ensure that a specified proportion of the products are covered within established acceptance limits. Exact two-sided parametric tolerance intervals are only available for the normal distribution, while exact one-sided parametric tolerance limits are available for a limited number of distributions. Approximations to two-sided parametric tolerance intervals often use the Bonferroni correction on the one-sided tolerance interval calculation; however, this often incurs a higher coverage probability than the nominal level. Recently, the usage of a bootstrap calibration has been demonstrated as a way to improve coverage probabilities of tolerance intervals for very specific and complex distributional settings. We present a focused treatment on using a single-layer bootstrap calibration to improve the coverage probabilities of two-sided parametric tolerance intervals. Simulation results clearly demonstrate the improved coverage probabilities towards the nominal level over the uncalibrated setting. Applications to medical data for various parametric distributions also highlight the utility of constructing these calibrated tolerance intervals.

Transcriptomic profiles of the bovine mammary gland during lactation and the dry period.

The initiation and maintenance of lactation are complex phenomena governed by biochemical and endocrine processes in the mammary gland (MG). Although DNA-based approaches have been used to study the onset of lactation, more comprehensive RNA-based techniques may be critical in furthering our understanding of gene alterations that occur to support lactation in the bovine MG. To further determine how gene profiles vary during lactation compared with the dry period, RNA-seq transcriptomic analysis was used to identify differentially expressed genes (DEG) in bovine MG tissues from animals that were lactating and not lactating. A total of 881 DEG (605 upregulated and 276 downregulated) were identified in MG of 3 lactating Chinese Holstein dairy cows versus the 3 dry cows. The subcellular analysis showed that the upregulated genes were most abundantly located in "integral to membrane" and "mitochondrion," and the top number of downregulated genes existed in "nucleus" and "cytoplasm." The functional analysis indicated that the DEG were primarily associated with the support of lactation processes. The genes in higher abundance were most related to "metabolic process," "oxidation-reduction process," "transport" and "signal transduction," protein synthesis-related processes (transcription, translation, protein modifications), and some MG growth-associated processes (cell proliferation/cycle/apoptosis). The downregulated genes were mainly involved in immune-related processes (inflammatory/immune/defense responses). The KEGG analysis suggested that protein synthesis-related pathways (such as protein digestion and absorption; protein processing in endoplasmic reticulum; and glycine, serine, and threonine metabolism) were highly and significantly enriched in the bovine MG of lactating cows compared to dry cows. The results suggested that the dry cows had decreased capacity for protein synthesis, energy generation, and cell growth but enhanced immune response. Collectively, this reduced capacity in dry cows supports the physiological demands of the next lactation and the coordinated metabolic changes that occur to support these demands. A total of 51 identified DEG were validated by RT-PCR, and consistent results were found between RT-PCR and the transcriptomic analysis. This work provides a profile of gene-associated changes that occur during lactation and can be used to facilitate further investigation of the mechanisms underlying lactation in dairy cows.

Lysine Stimulates Protein Synthesis by Promoting the Expression of ATB0,+ and Activating the mTOR Pathway in Bovine Mammary Epithelial Cells.

Background: l-lysine (Lys) is a critical dietary nutrient for mammary gland development and milk production. However, the specific pathways of Lys utilization and how milk protein synthesis is affected in bovine mammary epithelial cells (BMECs) are poorly understood. Objective: We aimed to investigate the effects of Lys on milk protein synthesis and the mechanism of Lys uptake and catabolism in BMECs. Methods: BMECs were cultured in 0, 0.5, 1.0, 1.5, 2.0, 5.0, and 10.0 mmol Lys/L to detect cell viability, or cultured in 0-2.0 mmol Lys/L with l-[ring-3H5] phenylalanine to study the effect of Lys on protein turnover, or cultured in Krebs buffer with [U-14C] l-Lys to quantify Lys metabolism. In some experiments, BMECs were cultured in a conditioned medium alone or including 1.0 mmol Lys/L and 2-amino-endo-bicyclo [2.2.1] heptane-2-carboxylic acid (BCH) for 24 h to analyze the expression of amino acid transporter B (0+) (ATB0,+), mammalian target of rapamycin (mTOR), and Janus kinase 2 (JAK2)-signal transducer and activator of transcription 5 (STAT5) pathways. Results: Including 1.0 mmol Lys/L in cultures increased cell viability by 17-47% and protein synthesis by 7-23%, whereas protein degradation was inhibited by 4-64% compared with BMECs cultured with 0, 0.5, or 2.0 mmol Lys/L (all P ≤ 0.05). Studies that used [U-14C] l-Lys showed that most Lys was incorporated into proteins (90%), whereas the remainder was either oxidized into CO2 (4%) or used as a substrate for aspartate (3%) and histidine synthesis (3%). Furthermore, Lys significantly increased expression of ATB0,+ (71% mRNA and 44% protein), STAT5 (27% mRNA and 21% phosphorylated proteins), and mTOR (51% mRNA and 22% phosphorylated proteins) compared with cells without Lys. Conclusions: Lys promoted protein synthesis, mostly through enhancing uptake by ATB0,+ and the mTOR and JAK2-STAT5 pathways. Understanding the utilization of Lys in BMECs provides insights into the role of amino acid nutrition in bovine milk production.

Population pharmacokinetics of exendin-(9-39) and clinical dose selection in patients with congenital hyperinsulinism.

AIMS: Congenital hyperinsulinism (HI) is the most common cause of persistent hypoglycaemia in infants and children. Exendin-(9-39), an inverse glucagon-like peptide 1 (GLP-1) agonist, is a novel therapeutic agent for HI that has demonstrated glucose-raising effect. We report the first population pharmacokinetic (PopPK) model of the exendin-(9-39) in patients with HI and propose the optimal dosing regimen for future clinical trials in neonates with HI. METHODS: A total of 182 pharmacokinetic (PK) observations from 26 subjects in three clinical studies were included for constructing the PopPK model using first order conditional estimation (FOCE) with interaction method in nonlinear mixed-effects modelling (NONMEM). Exposure metrics (area under the curve [AUC] and maximum plasma concentration [Cmax ]) at no observed adverse effect levels (NOAELs) in rats and dogs were determined in toxicology studies. RESULTS: Observed concentration-time profiles of exendin-(9-39) were described by a linear two-compartmental PK model. Following allometric scaling of PK parameters, age and creatinine clearance did not significantly affect clearance. The calculated clearance and elimination half-life for adult subjects with median weight of 69 kg were 11.8 l h-1 and 1.81 h, respectively. The maximum recommended starting dose determined from modelling and simulation based on the AUC0-last at the NOAEL and predicted AUC0-inf using the PopPK model was 27 mg kg-1  day-1 intravenously. CONCLUSIONS: This is the first study to investigate the PopPK of exendin-(9-39) in humans. The final PopPK model was successfully used with preclinical toxicology findings to propose the optimal dosing regimen of exendin-(9-39) for clinical studies in neonates with HI, allowing for a more targeted dosing approach to achieve desired glycaemic response.

The all-optical modulator in dielectric-loaded waveguide with graphene-silicon heterojunction structure.

All-optical modulators based on graphene show great promise for on-chip optical interconnects. However, the modulation performance of all-optical modulators is usually based on the interaction between graphene and the fiber, limiting their potential in high integration. Based on this point, an all-optical modulator in a dielectric-loaded waveguide (DLW) with a graphene-silicon heterojunction structure (GSH) is proposed. The DLW raises the waveguide mode, which provides a strong light-graphene interaction. Sufficient tuning of the graphene Fermi energy beyond the Pauli blocking effect is obtained with the presented GSH structure. Under the modulation light with a wavelength of 532 nm and a power of 60 mW, a modulation efficiency of 0.0275 dB µm-1 is achieved for light with a communication wavelength of 1.55 µm in the experiment. This modulator has the advantage of having a compact footprint, which may make it a candidate for achieving a highly integrated all-optical modulator.

Rapid screening and identification of targeted and non-targeted illegal added drugs in functional foods by MRSIT-HRMS based on NIST screening database.

The last few decades have witnessed the increasing consumption of functional foods, leading to the expansion of the worldwide market. However, the illegal addition drugs in functional foods remains incessant despite repeated prohibition, making it a key focus of strict crackdowns by regulatory authorities. Effective analytical tools and procedures are desperately needed to rapidly screen and identify illegally added drugs in a large number of samples, given the growing amount and diversity of these substances in functional foods. The MRSIT-HRMS (Multiple Sample Rapid Introduction combined with High Resolution Mass Spectrometry) without chromatographic separation, after direct sampling, utilizes NIST software (National Institute of Standards and Technology) matching with a home-built library to target identification and non-targeted screen of illegal additives. When applied to 50 batches of suspicious samples, the targeted method detected illegal added drugs in 41 batches of samples, while the non-targeted method screened a new phosphodiesterase-5 (PDE-5) inhibitor type structural derivative. The positive results obtained by the targeted method were consistent with LC-MS/MS (QQQ). The novel MRSIT-HRMS with a limit of quantification (LOD) of 1 µg/mL achieved 100 % correct identification for all 50 batches of actual samples, demonstrating its potential as a highly promising and powerful tool for fast screening of illegally added drugs in functional food, especially when compared to traditional LC-MS/MS methods. This is essential for ensuring drug safety and public health.

Diagnostic CT of colorectal cancer with artificial intelligence iterative reconstruction: A clinical evaluation.

OBJECTIVES: To investigate the clinical value of a novel deep-learning based CT reconstruction algorithm, artificial intelligence iterative reconstruction (AIIR), in diagnostic imaging of colorectal cancer (CRC). METHODS: This study retrospectively enrolled 217 patients with pathologically confirmed CRC. CT images were reconstructed with the AIIR algorithm and compared with those originally obtained with hybrid iterative reconstruction (HIR). Objective image quality was evaluated in terms of the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Subjective image quality was graded on the conspicuity of tumor margin and enhancement pattern as well as the certainty in diagnosing organ invasion and regional lymphadenopathy. In patients with surgical pathology (n = 116), the performance of diagnosing visceral peritoneum invasion was characterized using receiver operating characteristic (ROC) analysis. Changes of diagnostic thinking in diagnosing hepatic metastases were assessed through lesion classification confidence. RESULTS: The SNRs and CNRs on AIIR images were significantly higher than those on HIR images (all p < 0.001). The AIIR was scored higher for all subjective metrics (all p < 0.001) except for the certainty of diagnosing regional lymphadenopathy (p = 0.467). In diagnosing visceral peritoneum invasion, higher area under curve (AUC) of the ROC was found for AIIR than HIR (0.87 vs 0.77, p = 0.001). In assessing hepatic metastases, AIIR was found capable of correcting the misdiagnosis and improving the diagnostic confidence provided by HIR (p = 0.01). CONCLUSIONS: Compared to HIR, AIIR offers better image quality, improves the diagnostic performance regarding CRC, and thus has the potential for application in routine abdominal CT.

Flexible High-Temperature MoS2 Field-Effect Transistors and Logic Gates.

High-temperature-resistant integrated circuits with excellent flexibility, a high integration level (nanoscale transistors), and low power consumption are highly desired in many fields, including aerospace. Compared with conventional SiC high-temperature transistors, transistors based on two-dimensional (2D) MoS2 have advantages of superb flexibility, atomic scale, and ultralow power consumption. However, MoS2 cannot survive at high temperature and drastically degrades above 200 °C. Here, we report MoS2 field-effect transistors (FETs) with top/bottom hexagonal boron nitride (h-BN) encapsulation and graphene electrodes. With the protection of the h-BN/h-BN structure, the devices can survive at much higher temperature (≥500 °C in air) than those of the MoS2 devices ever reported, which provides us an opportunity to explore the electrical properties and working mechanism of MoS2 devices at high temperature. Unlike the relatively low-temperature situation, the on/off ratio and subthreshold swing of MoS2 FETs show drastic variation at elevated temperature due to the injection of thermal emission carriers. Compared with metal electrode, devices with a graphene electrode demonstrate superior performance at high temperature (∼1-order-larger current on/off ratio, 3-7 times smaller subthreshold swing, and 5-9 times smaller threshold voltage shift). We further realize that the flexible CMOS NOT gate based on the above technique, and demonstrate logic computing at 550 °C. This work may stimulate the fundamental research of properties of 2D materials at high temperature, and also creates conditions for next-generation flexible harsh-environment-resistant integrated circuits.

Evaluation of partial volume correction and analysis of longitudinal [18F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models.

Purpose: We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM). Methods: We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden-level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates. Results: The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability. Conclusion: The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test-retest variability. Clinical trial registration: NCT02640092 and NCT03289143.

Evaluation of Patient-Centric Sample Collection Technologies for Pharmacokinetic Assessment of Large and Small Molecules.

Low-volume sampling devices offer the promise of lower discomfort and greater convenience for patients, potentially reducing patient burden and enabling decentralized clinical trials. In this study, we determined whether low-volume sampling devices produce pharmacokinetic (PK) data comparable to conventional venipuncture for a diverse set of monoclonal antibodies (mAbs) and small molecules. We adopted an open-label, non-randomized, parallel-group, single-site study design, with four cohorts of 10 healthy subjects per arm. The study drugs, doses, and routes of administration included: crenezumab (15 mg/kg, intravenous infusion), etrolizumab (210 mg, subcutaneous), GDC-X (oral), and hydroxychloroquine (HCQ, 200 mg, oral). Samples were collected after administration of a single dose of each drug using conventional venipuncture and three low-volume capillary devices: TassoOne Plus for liquid blood, Tasso-M20 for dry blood, both applied to the arm, and Neoteryx Mitra® for dry blood obtained from fingertips. Serum/plasma concentrations from venipuncture and TassoOne Plus samples overlapped and PK parameters were comparable for all drugs, except HCQ. After applying a baseline hematocrit value, the dry blood concentrations and PK parameters for the two monoclonal antibodies were comparable to those obtained from venipuncture. For the two small molecules, two bridging strategies were evaluated for converting dry blood concentrations to equivalent plasma concentrations. A baseline hematocrit correction and/or linear regression-based correction was effective for GDC-X, but not for HCQ. Additionally, the study evaluated the bioanalytical data quality and comparability from the various collection methods, as well as patient preference for the devices.

Optofluidic crystallithography for directed growth of single-crystalline halide perovskites.

Crystallization is a fundamental phenomenon which describes how the atomic building blocks such as atoms and molecules are arranged into ordered or quasi-ordered structure and form solid-state materials. While numerous studies have focused on the nucleation behavior, the precise and spatiotemporal control of growth kinetics, which dictates the defect density, the micromorphology, as well as the properties of the grown materials, remains elusive so far. Herein, we propose an optical strategy, termed optofluidic crystallithography (OCL), to solve this fundamental problem. Taking halide perovskites as an example, we use a laser beam to manipulate the molecular motion in the native precursor environment and create inhomogeneous spatial distribution of the molecular species. Harnessing the coordinated effect of laser-controlled local supersaturation and interfacial energy, we precisely steer the ionic reaction at the growth interface and directly print arbitrary single crystals of halide perovskites of high surface quality, crystallinity, and uniformity at a high printing speed of 102 µm s-1. The OCL technique can be potentially extended to the fabrication of single-crystal structures beyond halide perovskites, once crystallization can be triggered under the laser-directed local supersaturation.

The endometrial microbiota profile influenced pregnancy outcomes in patients with repeated implantation failure: a retrospective study.

OBJECTIVES: To investigate the association between the pregnancy outcomes of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) patients with repeated implantation failure (RIF) and their endometrial microbiota profiles. METHODS: One hundred and forty-one RIF patients were recruited in this retrospective study. Endometrial tissues were sampled using a disposable sterile endometrium sampler. Comprehensive next-generation sequencing techniques were used to detect the endometrial bacteria status, and the pregnancy outcomes were analyzed. RESULTS: Endometrial pathogenic bacteria were detected in 125 patients (88.70%, the pathogenic group) while no relevant pathogen was found in the remaining 16 (11.30%, the no-pathogen group). All the 125 patients received the treatment of oral antibiotics for 14 days. Clinical pregnancy rates and ongoing pregnancy rates were higher in the pathogenic group than in the no-pathogen group without statistical significance (50.40% vs. 37.50%, P＞0.05; 42.40% vs. 25%, P＞0.05). CONCLUSION: In the endometrium of most RIF patients existed pathogenic bacteria, among which Streptococcus, Staphylococcus, Neisseria, and Klebsiella were most frequently observed, and the sensitive antibiotic therapy might improve clinical outcomes of the RIF patients in subsequent embryo transfer cycles.

A Survey of the Landscape Visibility Analysis Tools and Technical Improvements.

Visual perception of the urban landscape in a city is complex and dynamic, and it is largely influenced by human vision and the dynamic spatial layout of the attractions. In return, landscape visibility not only affects how people interact with the environment but also promotes regional values and urban resilience. The development of visibility has evolved, and the digital landscape visibility analysis method allows urban researchers to redefine visible space and better quantify human perceptions and observations of the landscape space. In this paper, we first reviewed and compared the theoretical results and measurement tools for spatial visual perception and compared the value of the analytical methods and tools for landscape visualization in multiple dimensions on the principal of urban planning (e.g., complex environment, computational scalability, and interactive intervention between computation and built environment). We found that most of the research was examined in a static environment using simple viewpoints, which can hardly explain the actual complexity and dynamic superposition of the landscape perceptual effect in an urban environment. Thus, those methods cannot effectively solve actual urban planning issues. Aiming at this demand, we proposed a workflow optimization and developed a responsive cross-scale and multilandscape object 3D visibility analysis method, forming our analysis model for testing on the study case. By combining the multilandscape batch scanning method with a refined voxel model, it can be adapted for large-scale complex dynamic urban visual problems. As a result, we obtained accurate spatial visibility calculations that can be conducted across scales from the macro to micro, with large external mountain landscapes and small internal open spaces. Our verified approach not only has a good performance in the analysis of complex visibility problems (e.g., we defined the two most influential spatial variables to maintain good street-based landscape visibility) but also the high efficiency of spatial interventions (e.g., where the four recommended interventions were the most valuable), realizing the improvement of intelligent landscape evaluations and interventions for urban spatial quality and resilience.

Two-Dimensional Transition Metal Dichalcogenide Tunnel Field-Effect Transistors for Biosensing Applications.

Field-effect transistor (FET) biosensors based on two-dimensional (2D) materials have drawn significant attention due to their outstanding sensitivity. However, the Boltzmann distribution of electrons imposes a physical limit on the subthreshold swing (SS), and a 2D-material biosensor with sub-60 mV/dec SS has not been realized, which hinders further increase of the sensitivity of 2D-material FET biosensors. Here, we report tunnel FETs (TFETs) based on a SnSe2/WSe2 heterostructure and observe the tunneling effect of a 2D material in aqueous solution for the first time with an ultralow SS of 29 mV/dec. A bilayer dielectric (Al2O3/HfO2) and graphene contacts, which significantly reduce the leakage current in solution and contact resistance, respectively, are crucial to the realization of the tunneling effect in solution. Then, we propose a novel biosensing method by using tunneling current as the sensing signal. The TFETs show an extremely high pH sensitivity of 895/pH due to ultralow SS, surpassing the sensitivity of FET biosensors based on a single 2D material (WSe2) by 8-fold. Specific detection of glucose is realized, and the biosensors show a superb sensitivity (3158 A/A for 5 mM), wide sensing range (from 10-9 to 10-3 M), low detection limit (10-9 M), and rapid response rate (11 s). The sensors also exhibit the ability of monitoring glucose in complex biofluid (sweat). This work provides a platform for ultrasensitive biosensing. The discovery of the tunneling effect of 2D materials in aqueous solution may stimulate further fundamental research and potential applications.

Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases.

Background: Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic value of quantitative high-resolution computed tomography (HRCT) metrics derived by Imbio lung texture analysis (LTA) tool in predicting FVC slope. Methods: This retrospective study used data from patients who were not treated with investigational drugs with and without background antifibrotic therapies in tocilizumab phase 3 SSc, lebrikizumab phase 2 IPF, and zinpentraxin alfa phase 2 IPF studies conducted from 2015 to 2021. Controlled HRCT axial volumetric multidetector computed tomography scans were evaluated using the Imbio LTA tool. Associations between HRCT metrics and FVC slope were assessed through the Spearman correlation coefficient and adjusted R2 in a linear regression model adjusted by demographics and baseline clinical characteristics. Results: A total of 271 SSc and IPF patients were analysed. Correlation coefficients of highest magnitude were observed in the SSc study between the extent of ground glass, normal volume, quantification of interstitial lung disease, reticular pattern, and FVC slope (-0.25, 0.28, -0.28, and -0.33, respectively), while the correlation coefficients observed in IPF studies were in general <0.2. The incremental prognostic value of the baseline HRCT metrics was marginal after adjusting baseline characteristics and was inconsistent across study arms. Conclusion: Data from the SSc and IPF studies suggested weak to no and inconsistent correlation between quantitative HRCT metrics derived by the Imbio LTA tool and FVC slope in the studied SSc and IPF population.

Protective effect of Du-Zhong-Wan against osteoporotic fracture by targeting the osteoblastogenesis and angiogenesis couple factor SLIT3.

ETHNOPHARMACOLOGICAL RELEVANCE: Du-Zhong-Wan (DZW) is a traditional Chinese medicine (TCM) composed of Eucommia ulmoides Oliv. and Dipsacus asper Wall. ex C.B. Clarke in the ratio 1:1. Based on the TCM theory, DZW nourishes the kidney to strengthen the bones. The literature research revealed that DZW possesses anti-fatigue, anti-depressant, and anti-osteoporotic properties. However, the action and mechanism of DZW on osteoporotic fracture remains slightly unclear. AIM OF THE STUDY: To evaluate the pharmacological effect of DZW on ovariectomized mice with an open femoral fracture and reveal the underlying mechanism. MATERIALS AND METHODS: We conducted ovariectomy for 5 weeks, followed by unilateral open transverse femoral fracture for another 3 weeks in C57BL/6 mice; during this process, DZW was administrated. The femur bone and vertebra tissues were collected and analyzed by micro-computed tomography, histomorphometry, mechanical strength testing, immunohistochemistry staining, and qRT-PCR analyses. In addition, alkaline phosphatase (ALP) and Alizarin red S (ARS) staining were performed to determine the extent of osteoblastogenesis from bone marrow mesenchymal stem cells (BMSCs). Western blotting was performed to examine the protein expression. RESULTS: DZW treatment significantly improved the bone histomorphometric parameters in mice undergoing ovariectomy when combined with the femoral fracture, including an increase in the bone volume, trabecular number, and bone formation rate and a decrease in the bone erosion area. Simultaneously, DZW treatment histologically promoted fractured callus formation. Mechanical strength testing revealed significantly higher stiffness and an ultimate load after treatment with DZW. The angiogenesis of H-type vessels was enhanced by DZW, as evidenced by increased levels of CD31 and endomucin (EMCN), the H-type vessel endothelium markers, at the fractured endosteum and metaphysis regions. Relative to the osteoporotic fracture mice, the DZW treatment group showed an increased proangiogenic factor SLIT3 level. The increased level of SLIT3 was also recorded during the process of DZW-stimulated osteoblastogenesis from BMSCs. CONCLUSIONS: For the first time, we demonstrated that DZW promoted osteoporotic fracture healing by enhancing osteoblastogenesis and angiogenesis of the H-type vessels. This enhanced combination of osteoblastogenesis and angiogenesis was possibly related to the production of proangiogenic factor SLIT3 induced by DZW.