A combination of risk stratification systems for thyroid nodules and cervical lymph nodes may improve the diagnosis and management of thyroid nodules.

Introduction: To assess the performance of the European Thyroid Association Thyroid Imaging and Reporting Data System (EU-TIRADS) and the Korean Thyroid Imaging Reporting and Data System (K-TIRADS), which combine risk stratification systems for thyroid nodules (TN-RSS) and cervical lymph nodes (LN-RSS) in diagnosing malignant and metastatic thyroid cancer in a single referral center. Methods: We retrospectively analyzed 2,055 consecutive patients who underwent thyroidectomy or fine-needle aspiration (FNA) from January 2021 to December 2022. TNs and LNs were categorized according to the ultrasonography (US) features of EU-TIRADS and K-TIRADS, respectively. The diagnostic performance and postponed malignancy rate (PMR) were compared with those of EU-TIRADS and K-TIRADS. PMR was defined as the number of patients with malignant nodules not recommended for biopsy among patients with cervical LN metastasis. Results: According to the EU-TIRADS and K-TIRADS, for TN-RSS alone, there were no significant differences in sensitivity, specificity, accuracy, unnecessary FNA rate (UFR), missed malignancy rate (MMR), and PMR between the two TIRADSs (29.0% vs. 28.8%, 50.5% vs. 51.1%, 32.3% vs. 32.2%, 23.6% vs. 23.5%, 88.6% vs. 88.5%, and 54.2% vs. 54.5%, P > 0.05 for all). Combining the LN-RSS increased the diagnostic accuracy (42.7% vs. 32.3% in EU-TIRADS; 38.8% vs. 32.2% in K-TIRADS) and decreased the PMR (54.2% vs. 33.9% in EU-TIRADS; 54.5% vs. 39.3% in K-TIRADS). EU-TIRADS had higher sensitivity and accuracy and lower PMR than K-TIRADS (41.3% vs. 36.7%, 42.7% vs. 38.8%,33.9% vs. 39.3%, P < 0.05 for all). Conclusions: A combination of TN-RSS and LN-RSS for the management of thyroid nodules may be associated with a reduction in PMR, with enhanced sensitivity and accuracy for thyroid cancers in EU-TIRADS and K-TIRADS. These results may offer a new direction for the detection of aggressive thyroid cancers.

PEX3 promotes regenerative repair after myocardial injury in mice through facilitating plasma membrane localization of ITGB3.

The peroxisome is a versatile organelle that performs diverse metabolic functions. PEX3, a critical regulator of the peroxisome, participates in various biological processes associated with the peroxisome. Whether PEX3 is involved in peroxisome-related redox homeostasis and myocardial regenerative repair remains elusive. We investigate that cardiomyocyte-specific PEX3 knockout (Pex3-KO) results in an imbalance of redox homeostasis and disrupts the endogenous proliferation/development at different times and spatial locations. Using Pex3-KO mice and myocardium-targeted intervention approaches, the effects of PEX3 on myocardial regenerative repair during both physiological and pathological stages are explored. Mechanistically, lipid metabolomics reveals that PEX3 promotes myocardial regenerative repair by affecting plasmalogen metabolism. Further, we find that PEX3-regulated plasmalogen activates the AKT/GSK3ß signaling pathway via the plasma membrane localization of ITGB3. Our study indicates that PEX3 may represent a novel therapeutic target for myocardial regenerative repair following injury.

ExtraTrees-hidden Markov model based equalizer for mode division multiplexing ring-core fiber communication with non-orthogonal MultiCAP modulation.

This paper presents an orbital angular momentum mode division multiplexing (OAM-MDM) ring-core fiber transmission method based on non-orthogonal multiband carrierless amplitude and phase (NMCAP) modulation with an extremely randomized trees-hidden Markov model (ExtraTrees-HMM)-based equalizer. The ExtraTrees-HMM equalizer uses the statistical characteristics of the received distorted signals to model the nonlinear channel of the system to classify these distorted signals into corresponding constellation classes. Experiments were conducted using a 216 Gbit/s OAM-MDM NMCAP modulation optical fiber communication system with 2 km ring-core fiber transmission and the results show that compared with a conventional Volterra nonlinear equalizer (VNE), the proposed ExtraTrees-HMM equalizer could improve the receiver sensitivity by 1 dB for OAM mode l = + 2, and 0.6 dB for OAM mode l = + 3. In addition, the computational complexity of the proposed equalizer was reduced by 43.94% compared with the VNE. In brief, the ExtraTrees-HMM is a promising equalization candidate for ultra-high-capacity inter-data-center interconnections.

End-to-end learning strategy based on a frequency domain feature decoupling network emulator with joint probabilistic shaping and equalization for a 300-Gbit/s OAM mode division multiplexing transmission.

Mode coupling and device nonlinear impairment appear to be a long-standing challenge in the orbital angular momentum (OAM) mode division multiplexing (MDM) of intensity modulation direct detection (IM/DD) transmission systems. In this paper, we propose an end-to-end (E2E) learning strategy based on a frequency domain feature decoupling network (FDFDnet) emulator with joint probabilistic shaping (PS) and equalization for an OAM-MDM IM/DD transmission with three modes. Our FDFDnet emulator can accurately build a complex nonlinear model of an OAM-MDM system by separating the signal into features from different frequency domains. Furthermore, a FDFDnet-based E2E strategy for joint PS and equalization is presented with the aim of compensating the signal impairment for the OAM-MDM IM/DD system. An experiment is carried out on a 300 Gbit/s carrierless amplitude phase-32 (CAP-32) signal with three OAM modes over a 10 km ring-core fiber transmission, and the results show that the proposed FDFDnet emulator outperforms the traditional CGAN emulator, with improvements in the modelling accuracy of 30.8%, 26.3% and 31% for the three OAM modes. Moreover, the receiver sensitivity of the proposed E2E learning strategy is higher than for the CGAN emulator by 3, 2.5, 2.2 dBm and the real channel by 5.5, 5.1, and 5.3 dBm for the three OAM modes, respectively. Our experimental results demonstrate that the proposed FDFDnet emulator-based E2E learning strategy is a promising contender for achieving ultra-high-capacity interconnectivity between data centers.

Improving both performance and stability of n-type organic semiconductors by vitamin C.

Organic semiconductors (OSCs) are one of the most promising candidates for flexible, wearable and large-area electronics. However, the development of n-type OSCs has been severely held back due to the poor stability of their most candidates, that is, the intrinsically high reactivity of negatively charged polarons to oxygen and water. Here we demonstrate a general strategy based on vitamin C to stabilize n-type OSCs, remarkably improving the performance and stability of their device, for example, organic field-effect transistors. Vitamin C scavenges reactive oxygen species and inhibits their generation by sacrificial oxidation and non-sacrificial triplet quenching in a cascade process, which not only lastingly prevents molecular structure from oxidation damage but also passivates the latent electron traps to stabilize electron transport. This study presents a way to overcome the long-standing stability problem of n-type OSCs and devices.

Genomic, transcriptomic, and metabolomic analyses provide insights into the evolution and development of a medicinal plant Saposhnikovia divaricata (Apiaceae).

Saposhnikovia divaricata, 2n = 2x = 16, as a perennial species, is widely distributed in China, Mongolia, Russia, etc. It is a traditional Chinese herb used to treat tetanus, rubella pruritus, rheumatic arthralgia, and other diseases. Here, we assembled a 2.07 Gb and N50 scaffold length of 227.67 Mb high-quality chromosome-level genome of S. divaricata based on the PacBio Sequel II sequencing platform. The total number of genes identified was 42 948, and 42 456 of them were functionally annotated. A total of 85.07% of the genome was composed of repeat sequences, comprised mainly of long terminal repeats (LTRs) which represented 73.7% of the genome sequence. The genome size may have been affected by a recent whole-genome duplication event. Transcriptional and metabolic analyses revealed bolting and non-bolting S. divaricata differed in flavonoids, plant hormones, and some pharmacologically active components. The analysis of its genome, transcriptome, and metabolome helped to provide insights into the evolution of bolting and non-bolting phenotypes in wild and cultivated S. divaricata and lays the basis for genetic improvement of the species.

Development and biomechanical analysis of an axially controlled compression spinal rod for lumbar spondylolysis.

BACKGROUND: To elucidate the differences in mechanical performance between a novel axially controlled compression spinal rod (ACCSR) for lumbar spondylolysis (LS) and the common spinal rod (CSR). METHODS: A total of 36 ACCSRs and 36 CSRs from the same batch were used in this study, each with a diameter of 6.0 mm. Biomechanical tests were carried out on spinal rods for the ACCSR group and on pedicle screw-rod internal fixation systems for the CSR group. The spinal rod tests were conducted following the guidelines outlined in the American Society for Testing and Materials (ASTM) F 2193, while the pedicle screw-rod internal fixation system tests adhered to ASTM F 1798-97 standards. RESULTS: The stiffness of ACCSR and CSR was 1559.15 ±â€…50.15 and 3788.86 ±â€…156.45 N/mm (P < .001). ACCSR's yield load was 1345.73 (1297.90-1359.97) N, whereas CSR's was 4046.83 (3805.8-4072.53) N (P = .002). ACCSR's load in the 2.5 millionth cycle of the fatigue four-point bending test was 320 N. The axial gripping capacity of ACCSR and CSR was 1632.53 ±â€…165.64 and 1273.62 ±â€…205.63 N (P = .004). ACCSR's torsional gripping capacity was 3.45 (3.23-3.47) Nm, while CSR's was 3.27 (3.07-3.59) Nm (P = .654). The stiffness of the pedicle screws of the ACCSR and CSR group was 783.83 (775.67-798.94) and 773.14 (758.70-783.62) N/mm (P = .085). The yield loads on the pedicle screws of the ACCSR and CSR group was 1345.73 (1297.90-1359.97) and 4046.83 (3805.8-4072.53) N (P = .099). CONCLUSION: Although ACCSR exhibited lower yield load, stiffness, and fatigue resistance compared to CSR, it demonstrated significantly higher axial gripping capacity and met the stress requirement of the human isthmus. Consequently, ACCSR presents a promising alternative to CSR for LS remediation.

Deep Learning Radiomics Model of Contrast-Enhanced CT for Differentiating the Primary Source of Liver Metastases.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CT) to identify the primary source of liver metastases. MATERIALS AND METHODS: In total, 657 liver metastatic lesions, including breast cancer (BC), lung cancer (LC), colorectal cancer (CRC), gastric cancer (GC), and pancreatic cancer (PC), from 428 patients were collected at three clinical centers from January 2018 to October 2023 series. The lesions were randomly assigned to the training and validation sets in a 7:3 ratio. An additional 112 lesions from 61 patients at another clinical center served as an external test set. A DLR model based on contrast-enhanced CT of the liver was developed to distinguish the five pathological types of liver metastases. Stepwise classification was performed to improve the classification efficiency of the model. Lesions were first classified as digestive tract cancer (DTC) and non-digestive tract cancer (non-DTC). DTCs were divided into CRC, GC, and PC and non-DTCs were divided into LC and BC. To verify the feasibility of the DLR model, we trained classical machine learning (ML) models as comparison models. Model performance was evaluated using accuracy (ACC) and area under the receiver operating characteristic curve (AUC). RESULTS: The classification model constructed by the DLR algorithm showed excellent performance in the classification task compared to ML models. Among the five categories task, highest ACC and average AUC were achieved at 0.563 and 0.796 in the validation set, respectively. In the DTC and non-DTC and the LC and BC classification tasks, AUC was achieved at 0.907 and 0.809 and ACC was achieved at 0.843 and 0.772, respectively. In the CRC, GC, and PC classification task, ACC and average AUC were the highest, at 0.714 and 0.811, respectively. CONCLUSION: The DLR model is an effective method for identifying the primary source of liver metastases.

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication.

BACKGROUND: Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety. METHODS: Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset. RESULTS: The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets. LIMITATIONS: The use of cross-sectional data limited the inferences about the direction of causality between variables. CONCLUSIONS: These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.

Superionic fluoride gate dielectrics with low diffusion barrier for two-dimensional electronics.

Exploration of new dielectrics with a large capacitive coupling is an essential topic in modern electronics when conventional dielectrics suffer from the leakage issue near the breakdown limit. Here, to address this looming challenge, we demonstrate that rare-earth metal fluorides with extremely low ion migration barriers can generally exhibit an excellent capacitive coupling over 20 µF cm-2 (with an equivalent oxide thickness of ~0.15 nm and a large effective dielectric constant near 30) and great compatibility with scalable device manufacturing processes. Such a static dielectric capability of superionic fluorides is exemplified by MoS2 transistors exhibiting high on/off current ratios over 108, ultralow subthreshold swing of 65 mV dec-1 and ultralow leakage current density of ~10-6 A cm-2. Therefore, the fluoride-gated logic inverters can achieve notably higher static voltage gain values (surpassing ~167) compared with a conventional dielectric. Furthermore, the application of fluoride gating enables the demonstration of NAND, NOR, AND and OR logic circuits with low static energy consumption. In particular, the superconductor-insulator transition at the clean-limit Bi2Sr2CaCu2O8+δ can also be realized through fluoride gating. Our findings highlight fluoride dielectrics as a pioneering platform for advanced electronic applications and for tailoring emergent electronic states in condensed matter.

Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images - Nevus & Melanoma.

Automated region of interest detection in histopathological image analysis is a challenging and important topic with tremendous potential impact on clinical practice. The deep-learning methods used in computational pathology may help us to reduce costs and increase the speed and accuracy of cancer diagnosis. We started with the UNC Melanocytic Tumor Dataset cohort that contains 160 hematoxylin and eosin whole-slide images of primary melanomas (86) and nevi (74). We randomly assigned 80% (134) as a training set and built an in-house deep-learning method to allow for classification, at the slide level, of nevi and melanomas. The proposed method performed well on the other 20% (26) test dataset; the accuracy of the slide classification task was 92.3% and our model also performed well in terms of predicting the region of interest annotated by the pathologists, showing excellent performance of our model on melanocytic skin tumors. Even though we tested the experiments on the skin tumor dataset, our work could also be extended to other medical image detection problems to benefit the clinical evaluation and diagnosis of different tumors.

Trilaciclib dosage in Chinese patients with extensive-stage small cell lung cancer: a pooled pharmacometrics analysis.

This study aimed to analyze potential ethnic disparities in the dose-exposure-response relationships of trilaciclib, a first-in-class intravenous cyclin-dependent kinase 4/6 inhibitor for treating chemotherapy-induced myelosuppression in patients with extensive-stage small cell lung cancer (ES-SCLC). This investigation focused on characterizing these relationships in both Chinese and non-Chinese patients to further refine the dosing regimen for trilaciclib in Chinese patients with ES-SCLC. Population pharmacokinetic (PopPK) and exposure-response (E-R) analyses were conducted using pooled data from four randomized phase 2/3 trials involving Chinese and non-Chinese patients with ES-SCLC. PopPK analysis revealed that trilaciclib clearance in Chinese patients was approximately 17% higher than that in non-Chinese patients with ES-SCLC. Sex and body surface area influenced trilaciclib pharmacokinetics in both populations but did not exert a significant clinical impact. E-R analysis demonstrated that trilaciclib exposure increased with a dosage escalation from 200 to 280 mg/m2, without notable changes in myeloprotective or antitumor efficacy. However, the incidence of infusion site reactions, headaches, and phlebitis/thrombophlebitis rose with increasing trilaciclib exposure in both Chinese and non-Chinese patients with ES-SCLC. These findings suggest no substantial ethnic disparities in the dose-exposure-response relationship between Chinese and non-Chinese patients. They support the adoption of a 240-mg/m2 intravenous 3-day or 5-day dosing regimen for trilaciclib in Chinese patients with ES-SCLC.

Magnetic field-assisted surface engineering technology for active regulation of Fe3O4 medium to enable the laccase electrochemical biosensing of catechol with visible stripe patterns.

BACKGROUND: Catechol (CC), a prevalent phenolic compound, is a byproduct in various agricultural, chemical, and industrial processes. CC detection is crucial for safeguarding water quality and plays a pivotal role in enhancing the overall quality of life of individuals. Electrochemical biosensors exhibit rapid responses, have small sizes, and can be used for real-time monitoring. Therefore, the development of a fast and sensitive electrochemical biosensor for CC detection is crucial. RESULT: In this study, a laccase-based electrochemical biosensor for detection of CC is successfully developed using Fe3O4 nanoparticles as medium and optimized by applying a magnetic field. This research proposes a unique strategy for biosensor enhancement by actively controlling the distribution of magnetic materials on the electrode surface through the application of a magnetic field, resulting in a visibly alternating stripe pattern. This approach effectively disperses magnetic particles, preventing their aggregation and reducing the boundary layer thickness, enhancing the electrochemical response of the biosensor. After fabrication condition optimization, CC is successfully detected using this biosensor. The fabricated sensor exhibits excellent performance with a wide linear detection range of 10-1000 µM, a low detection limit of 1.25 µM, and a sensitivity of 7.9 µA/mM. The fabricated sensor exhibits good selectivity and reliable detection in real water samples. In addition, the laccase-based sensor has the potential for the fast and accurate monitoring of CC in olive oil. SIGNIFICANCE: The magnetic field optimization in this study significantly improved the performance of the electrochemical biosensor for detecting CC in environmental samples. Overall, the sensor developed in this study has the potential for fast and accurate monitoring of CC in environmental samples, highlighting the potential importance of a magnetic field environment in improving the performance of catechol electrochemical biosensors.

Ultrasonic-assisted green extraction and incorporation of Spirulina platensis bioactive components into turmeric essential oil-in-water nanoemulsion for enhanced antioxidant and antimicrobial activities.

The utilization of essential oils as natural antioxidants and preservatives is limited by high volatility, poor water solubility, and long-term instability. To address this, a novel ultrasonic-assisted method was used to prepare and stabilize a nanoemulsion of turmeric essential oil-in-water, incorporating bioactive components extracted from Spirulina platensis. Ultrasonic treatment enhanced the extraction efficacy and nanoemulsion stability. Algal biomass subjected to ultrasonic treatment (30 min at 80% amplitude) yielded a dry extract of 73.66 ± 3.05%, with the highest protein, phenolic, phycocyanin, and allophycocyanin content, as well as maximum emulsifying activity. The resulting nanoemulsion (5% oil, 0.3% extract, 10 min ultrasonic treatment) showed reduced particle size (173.31 ± 2.24 nm), zeta potential (-36.33 ± 1.10 mV), low polydispersity index, and enhanced antioxidant and antibacterial properties. Rheology analysis indicated shear-thinning behavior, while microscopy and spectroscopy confirmed structural changes induced by ultrasonic treatment and extract concentration. This initiative developed a novel ultrasonic-assisted algal-based nanoemulsion with antioxidant and antibacterial properties.

Establishment of a two-hit mouse model of environmental factor induced autism spectrum disorder.

Autism spectrum disorder (ASD) is a group of developmental diseases characterized by social dysfunction and repetitive stereotype behaviors. Besides genetic mutations, environmental factors play important roles in the development of ASD. Valproic acid (VPA) is widely used for modeling environmental factor induced ASD in rodents. However, traditional VPA modeling is low-in-efficiency and the phenotypes often vary among different batches of experiments. To optimize this ASD-modeling method, we tested "two-hit" hypothesis by single or double exposure of VPA and poly:IC at the critical time points of embryonic and postnatal stage. The autistic-like behaviors of mice treated with two-hit schemes (embryonic VPA plus postnatal poly:IC, embryonic poly:IC plus postnatal VPA, embryonic VPA plus poly: IC, or postnatal VPA plus poly:IC) were compared with mice treated with traditional VPA protocol. The results showed that all single-hit and two-hit schemes produced core ASD phenotypes as VPA single treatment did. Only one group, namely, mice double-hit by VPA and poly:IC simultaneously at E12.5 showed severe impairment of social preference, social interaction and ultrasonic communication, as well as significant increase of grooming activity and anxiety-like behaviors, in comparation with mice treated with the traditional VPA protocol. These data demonstrated that embryonic two-hit of VPA and poly:IC is more efficient in producing ASD phenotypes in mice than the single-hit of VPA, indicating this two-hit scheme could be utilized for modeling environmental factors induced ASD.

Molecular tuning boosts asymmetric C-C coupling for CO conversion to acetate.

Electrochemical carbon dioxide/carbon monoxide reduction reaction offers a promising route to synthesize fuels and value-added chemicals, unfortunately their activities and selectivities remain unsatisfactory. Here, we present a general surface molecular tuning strategy by modifying Cu2O with a molecular pyridine-derivative. The surface modified Cu2O nanocubes by 4-mercaptopyridine display a high Faradaic efficiency of greater than 60% in electrochemical carbon monoxide reduction reaction to acetate with a current density as large as 380 mA/cm2 in a liquid electrolyte flow cell. In-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy reveals stronger *CO signal with bridge configuration and stronger *OCCHO signal over modified Cu2O nanocubes by 4-mercaptopyridine than unmodified Cu2O nanocubes during electrochemical CO reduction. Density function theory calculations disclose that local molecular tuning can effectively regulate the electronic structure of copper catalyst, enhancing *CO and *CHO intermediates adsorption by the stabilization effect through hydrogen bonding, which can greatly promote asymmetric *CO-*CHO coupling in electrochemical carbon monoxide reduction reaction.

Treatment advances in high-grade gliomas.

High-grade gliomas (HGG) pose significant challenges in modern tumour therapy due to the distinct biological properties and limitations of the blood-brain barrier. This review discusses recent advancements in HGG treatment, particularly in the context of immunotherapy and cellular therapy. Initially, treatment strategies focus on targeting tumour cells guided by the molecular characteristics of various gliomas, encompassing chemotherapy, radiotherapy and targeted therapy for enhanced precision. Additionally, technological enhancements are augmenting traditional treatment modalities. Furthermore, immunotherapy, emphasising comprehensive tumour management, has gained widespread attention. Immune checkpoint inhibitors, vaccines and CAR-T cells exhibit promising efficacy against recurrent HGG. Moreover, emerging therapies such as tumour treating fields (TTFields) offer additional treatment avenues for patients with HGG. The combination of diverse treatments holds promise for improving the prognosis of HGG, particularly in cases of recurrence.

Prenatal ultrasound findings and clinical outcomes of uniparental disomy: a retrospective study.

BACKGROUND: Uniparental disomy is the inheritance of a homologous chromosome pair or part of homologous chromosomes from only one parent. However, the clinical significance of uniparental disomy and the difference among the prognosis of involvement of different chromosomes remain unclear. OBJECTIVE: To assess the associated prenatal ultrasound presentations and clinical outcomes of uniparental disomy on different chromosomes and to analyze the relationship between prenatal ultrasound markers and clinical outcomes. STUDY DESIGN: We retrospectively analyzed data from fetuses with uniparental disomy diagnosed using chromosome microarray analysis with the Affymetrix CytoScan HD array at our institution between January 2013 and September 2022. The relationship between prenatal ultrasound findings, the involved chromosome(s), and clinical outcomes was evaluated. RESULTS: During the study period, 36 fetuses with uniparental disomy were diagnosed, and two cases were excluded for non-available postnatal data. Finally, 34 fetuses were included in our study, of which 30 (88.2%) had uniparental disomy occurring on a single chromosome, while four (11.8%) were identified with uniparental disomy on different chromosomes. The most frequently involved chromosomes were chromosomes 16, X and 2, which presented in 8 (23.5%), 5 (14.7%) and 4 (11.8%), respectively. Prenatal ultrasound abnormalities were detected in 21 fetuses, with the most common category being multiple abnormalities (12 (57.1%)). Fetal growth restriction was identified in 14 (41.2%) fetuses, all of which coexisted with other abnormal findings. The rate of adverse perinatal outcomes in patients with uniparental disomy and fetal abnormalities was significantly higher than those without abnormalities (76.2% versus 15.4%, P = 0.002). The incidence of fetal or neonatal death was significantly higher in fetuses with fetal growth restriction than those without (85.7% versus 30.0%, P = 0.004). CONCLUSIONS: The prognosis of fetuses with uniparental disomy combined with fetal abnormalities, especially fetal growth restriction, was much poorer than those without.

Evolution and Interplay of Lithium Metal Interphase Components Revealed by Experimental and Theoretical Studies.

Lithium metal batteries (LMB) have high energy densities and are crucial for clean energy solutions. The characterization of the lithium metal interphase is fundamentally and practically important but technically challenging. Taking advantage of synchrotron X-ray, which has the unique capability of analyzing crystalline/amorphous phases quantitatively with statistical significance, we study the composition and dynamics of the LMB interphase for a newly developed important LMB electrolyte that is based on fluorinated ether. Pair distribution function analysis revealed the sequential roles of the anion and solvent in interphase formation during cycling. The relative ratio between Li2O and LiF first increases and then decreases during cycling, suggesting suppressed Li2O formation in both initial and long extended cycles. Theoretical studies revealed that in initial cycles, this is due to the energy barriers in many-electron transfer. In long extended cycles, the anion decomposition product Li2O encourages solvent decomposition by facilitating solvent adsorption on Li2O which is followed by concurrent depletion of both. This work highlights the important role of Li2O in transitioning from an anion-derived interphase to a solvent-derived one.

Advances in Adjoint Functions of Connection Number in Water Resources Complex Systems: A Systematic Review.

The adjoint function of connection number has unique advantages in solving uncertainty problems of water resource complex systems, and has become an important frontier and research hotspot in the uncertainty research of water resource complex problems. However, in the rapid evolution of the adjoint function, some problems greatly limit the application of the adjoint function in the research of water resources. Therefore, based on bibliometric analysis, development, practical application issues, and prospects of the hot directions are analyzed. It is found that the development of the connection number of water resource set pair analysis can be divided into three stages: (1) relatively sluggish development before 2005, (2) a period of rapid advancement in adjoint function research spanning from 2005 to 2017, and (3) a subsequent surge post-2018. The introduction of the adjoint function of connection number promotes the continuous development of set pair analysis of water resources. Set pair potential and partial connection number are the crucial research directions of the adjoint function. Subtractive set pair potential has rapidly developed into a relatively independent and important trajectory. The research on connection entropy is comparatively less, which needs to be further strengthened, while that on adjacent connection number is even less. The adjoint function of set pair potential can be divided into three major categories: division set pair potential, exponential set pair potential, and subtraction set pair potential. The subtraction set pair potential, which retains the original dimension and quantity variation range of the connection number, is widely used in water resources and other fields. Coupled with the partial connection number, a series of new connection number adjoint functions have been developed. The partial connection number can be mainly divided into two categories: total partial connection number, and semi-partial connection number. Among these, the calculation expression and connotation of total partial connection numbers have not yet reached a consensus, accompanied by the slow development of high-order partial connection numbers. Semi-partial connection number can describe the mutual migration movement between different components of the connection number, which develops rapidly. With the limitations and current situation described above, promoting the exploration and application of the adjoint function of connection number in the field of water resources and other fields of complex systems has become the focus of future research.