Growth mechanisms and anisotropic softness-dependent conductivity of orientation-controllable metal-organic framework nanofilms.

Conductive metal-organic frameworks (cMOFs) manifest great potential in modern electrical devices due to their porous nature and the ability to conduct charges in a regular network. cMOFs applied in electrical devices normally hybridize with other materials, especially a substrate. Therefore, the precise control of the interface between cMOF and a substrate is particularly crucial. However, the unexplored interface chemistry of cMOFs makes the controlled synthesis and advanced characterization of high-quality thin films, particularly challenging. Herein, we report the development of a simplified synthesis method to grow "face-on" and "edge-on" cMOF nanofilms on substrates, and the establishment of operando characterization methodology using atomic force microscopy and X-ray, thereby demonstrating the relationship between the soft structure of surface-mounted oriented networks and their characteristic conductive functions. As a result, crystallinity of cMOF nanofilms with a thickness down to a few nanometers is obtained, the possible growth mechanisms are proposed, and the interesting anisotropic softness-dependent conducting properties (over 2 orders of magnitude change) of the cMOF are also illustrated.

Biallelic variants in α-tubulin isotypes cause female infertility characterised as recurrent preimplantation embryo arrest.

BACKGROUND: Recurrent preimplantation embryo developmental arrest (RPEA) is the most common phenotype in assisted reproductive technology treatment failure associated with identified genetic abnormalities. Currently known maternal genetic variants explain only a limited number of cases. Variants of the ß-tubulin subunit gene, TUBB8, cause oocyte meiotic arrest and RPEA through a broad spectrum of spindle defects. In contrast, α-tubulin subunit genes are poorly studied in the context of preimplantation embryonic development. METHODS: Whole exome sequencing was performed on the PREA cohort. Functional characterisations of the identified candidate disease-causing variants were validated using Sanger sequencing, bioinformatics, in vitro functional analyses and single-cell RNA-sequencing of arrested embryos. RESULTS: Four homozygous variants were identified in the PREA cohort: two of TUBA1C (p.Gln358Ter and p.Asp444Metfs*42) and two of TUBA4A (p.Arg339Cys and p.Tyr440Ter). These variants cause varying degrees of spindle assembly defects. Additionally, we characterised changes in the human arrested embryo transcriptome carrying TUBA4A variants, with a particular focus on spindle organisation, chromosome segregation and mRNA decay. CONCLUSION: Our findings identified TUBA1C as a novel genetic marker and expanded the genetic and phenotypic spectrum of TUBA4A in female infertility and RPEA, which altogether highlighted the importance of α-tubulin isotypes in preimplantation embryonic development.

Homozygous pathogenic variants in ACTL9 cause fertilization failure and male infertility in humans and mice.

Total fertilization failure (TFF) can occur during in vitro fertilization (IVF) treatments, even following intracytoplasmic sperm injection (ICSI). Various male or female factors could contribute to TFF. Increasing evidence suggested that genetic variations in PLCZ1, which encodes 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase zeta-1 (PLCζ), is involved in oocyte activation and is a key male factor in TFF. In the present study, we explored the genetic variants in male individuals that led to TFF. A total of 54 couples with TFF or poor fertilization (fertilization rate < 20%) were screened, and 21 couples were determined to have a male infertility factor by the mouse oocyte activation test. Whole-exome sequencing of these 21 male individuals identified three homozygous pathogenic variants in ACTL9 (actin like 9) in three individuals. ACTL9 variations led to abnormal ultrastructure of the perinuclear theca (PT), and PLCζ was absent in the head and present in the neck of the mutant sperm, which contributed to failed normal calcium oscillations in oocytes and subsequent TFF. The key roles of ACTL9 in the PT structure and TFF after ICSI were further confirmed in an Actl9-mutated mouse model. Furthermore, assisted oocyte activation by calcium ionophore exposure successfully overcame TFF and achieved live births in a couple with an ACTL9 variant. These findings identified the role of ACTL9 in the PT structure and the correct localization of PLCζ. The results also provide a genetic marker and a therapeutic option for individuals who have undergone ICSI without successful fertilization.

Liquid Metal Interlayer for Ultrastable Solid-State Sodium Metal Battery.

Solid-state sodium metal batteries have attracted wide attention due to their high energy density, remarkable safety, and abundant sodium resources. However, the growth of Na dendrites and poor interfacial contact between Na metal anode and Na3Zr2Si2PO12 (NZSP) solid-state electrolytes severely limit their practical application. Herein, a wettable liquid metal (GaIn) interlayer significantly reduces the interfacial resistance and avoids the formation of voids at the Na/NZSP interface. Moreover, the Ga4Na and NaIn alloys at the interface caused by the spontaneous reaction of GaIn with Na metal enhance the bond of NZSP with Na anode, which provides a continuous Na+ diffusion pathway and homogeneous Na+ flux to suppress Na dendrite growth. The symmetric cell can cycle stably for over 6500 h at 0.05 mA cm-2 and over 3000 h at 0.1 mA cm-2, with a critical current density of 0.8 mA cm-2 at 25 °C, and the interfacial resistance is significantly reduced to 21.6 Ω from 1095.1 Ω. The full cell coupled with NaNi1/3Fe1/3Mn1/3O2 also shows outstanding cycling performance, maintaining 85.1% capacity after 100 cycles at 0.5 C. This work demonstrates that the liquid metal interlayer has a large potential for the practical application of solid-state metal batteries.

Testing the generalizability and effectiveness of deep learning models among clinics: sperm detection as a pilot study.

BACKGROUND: Deep learning has been increasingly investigated for assisting clinical in vitro fertilization (IVF). The first technical step in many tasks is to visually detect and locate sperm, oocytes, and embryos in images. For clinical deployment of such deep learning models, different clinics use different image acquisition hardware and different sample preprocessing protocols, raising the concern over whether the reported accuracy of a deep learning model by one clinic could be reproduced in another clinic. Here we aim to investigate the effect of each imaging factor on the generalizability of object detection models, using sperm analysis as a pilot example. METHODS: Ablation studies were performed using state-of-the-art models for detecting human sperm to quantitatively assess how model precision (false-positive detection) and recall (missed detection) were affected by imaging magnification, imaging mode, and sample preprocessing protocols. The results led to the hypothesis that the richness of image acquisition conditions in a training dataset deterministically affects model generalizability. The hypothesis was tested by first enriching the training dataset with a wide range of imaging conditions, then validated through internal blind tests on new samples and external multi-center clinical validations. RESULTS: Ablation experiments revealed that removing subsets of data from the training dataset significantly reduced model precision. Removing raw sample images from the training dataset caused the largest drop in model precision, whereas removing 20x images caused the largest drop in model recall. by incorporating different imaging and sample preprocessing conditions into a rich training dataset, the model achieved an intraclass correlation coefficient (ICC) of 0.97 (95% CI: 0.94-0.99) for precision, and an ICC of 0.97 (95% CI: 0.93-0.99) for recall. Multi-center clinical validation showed no significant differences in model precision or recall across different clinics and applications. CONCLUSIONS: The results validated the hypothesis that the richness of data in the training dataset is a key factor impacting model generalizability. These findings highlight the importance of diversity in a training dataset for model evaluation and suggest that future deep learning models in andrology and reproductive medicine should incorporate comprehensive feature sets for enhanced generalizability across clinics.

Regulation Mechanism for Designing Decarbonization Pathways in the Copper Industry Toward Carbon Neutrality.

The transformation of the global power structure caused by the carbon neutrality goal will promote copper consumption. It is crucial to explore the decarbonization pathways of the copper industry to help fulfill greenhouse gas (GHG) emission reduction targets. This study utilized material flow analysis and life cycle assessment methods to investigate 12 different subscenarios based on international trade, circular economy, technology evolution, and environmental market factors. Policy combination scenario is employed to reveal the mechanism of decarbonization. The results show that refined copper consumption in China is expected to increase by 62.3% in 2060 compared to 2020. The GHG emissions of China's copper industry will reach 9.1 million tonnes (Mt) CO2e in 2060, technology evolution and environmental market are crucial for realizing carbon neutrality goal of this industry, accounting for 26.4 and 47.2% of emissions reductions, respectively, between 2020 and 2060. International trade and circular economy play important roles in the high-quality carbon peaking stage; however, imported copper and domestic secondary copper will constitute the basic supply of copper resources in China in the long run, and the comparative advantages of them will gradually weaken. Policy combination scenario can achieve the incentive synergy effect, with GHG reduced to 0.5 Mt CO2e in 2060. The enhanced application of policies such as material substitution and carbon emission trading will further promote industry to achieve net-zero GHG emission. We suggest regulating the industry's structure based on the international systemic circulation pattern and accelerating the construction of a green circular chain in the short term to achieve sustainable copper supply and high-quality carbon peaking. Promoting a high-quality technology development strategy and enhancing the environmental markets are recommended in the long term to achieve carbon neutrality.

Prognostic nomogram for patients with tongue squamous cell carcinoma: A SEER-based study.

OBJECTIVES: In order to predict the patients' prognosis with tongue squamous cell carcinoma (SCC), this study set out to develop a clinically useful and trustworthy prognostic nomogram. SUBJECTS AND METHODS: The Surveillance, Epidemiology, and End Results (SEER) Program was used to compile clinical information on patients with tongue SCC between 2010 and 2015. The likelihood of Cancer-Specific Survival (CSS) and Overall Survival (OS) for specific patients was predicted using a prognostic nomogram created with the help of the RStudio software. The nomogram's predictive ability was evaluated using the consistency index (C-index) and decision curve analysis, and the nomogram was calibrated for 1-, 2-, 3-, 5-, and 10-year CSS and OS. RESULTS: Patients numbering 6453were enrolled in this study. The primary cohort (3895) and validation cohort (2558) were each randomly assigned. Sex, age, tumor-node-metastasis (TNM) stage, surgery, chemotherapy, and radiation were significant risk factors for OS, whereas age, TNM stage, surgery, chemotherapy, and radiotherapy were significant risk factors for CSS. Additionally, C-index and calibration curves indicated that the prognostic nomogram prediction and the actual observation in both cohorts would be very coherent. CONCLUSIONS: The predictive nomogram created in this study can offer patients with tongue SCC customized treatment and survival risk assessment.

Very severe oligozoospermia with AZFc microdeletion patients may affect intracytoplasmic sperm injection clinical outcomes: A propensity score matching analysis.

Purpose: To explore whether spermatozoa from AZFc microdeletion patients affect their outcomes of intracytoplasmic sperm injection (ICSI). Methods: Eighty-five patients with AZFc microdeletion were recruited. A control group of one hundred and forty patients with severe oligozoospermia but without AZF microdeletion was selected using propensity score matching analysis with a 1:2 nearest neighbor algorithm ratio. The ICSI outcomes of the two groups were compared. Results: AZFc microdeletion had lower rates of normal fertilization (73% vs. 80%, p = 0.17) and high-quality embryos (44% vs. 58%, p = 0.07) than the control group. There was no significant difference in the clinical pregnancy rate, miscarriage rate, and live birth rate between the two groups. When the sperm concentration was <1 million/mL, the AZFc microdeletion group exhibited lower rates of fertilization (71% vs. 80%, p = 0.03), high-quality embryo (44% vs. 58%, p = 0.02), clinical pregnancy (57% vs. 76%, p = 0.02), and live birth (49% vs. 72%, p = 0.01) than the control group. However, if sperm concentration was ≥1 million/mL, no significant differences were found. Conclusion: If the sperm concentration is <1 million/mL, AZFc microdeletion do have a detrimental effect on most outcomes of ICSI.

High Sensitivity, Wide Linear-Range Strain Sensor Based on MXene/AgNW Composite Film with Hierarchical Microcrack.

Stretchable strain sensors suffer the trade-off between sensitivity and linear sensing range. Developing sensors with both high sensitivity and wide linear range remains a formidable challenge. Different from conventional methods that rely on the structure design of sensing nanomaterial or substrate, here a heterogeneous-surface strategy for silver nanowires (AgNWs) and MXene is proposed to construct a hierarchical microcrack (HMC) strain sensor. The heterogeneous surface with distinct differences in cracks and adhesion strengths divides the sensor into two regions. One region contributes to high sensitivity through penetrating microcracks of the AgNW/MXene composite film during stretching. The other region maintains conductive percolation pathways to provide a wide linear sensing range through network microcracks. As a result, the HMC sensor exhibits ultrahigh sensitivity (gauge factor ≈ 244), broad linear range (ɛ = 60%, R2 ≈ 99.25%), and fast response time (<30 ms). These merits are confirmed in the detection of large and subtle human motions and digital joint movement for Morse coding. The manipulation of cracks on the heterogeneous surface provides a new paradigm for designing high-performance stretchable strain sensors.

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection.

BACKGROUND: To develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features. METHODS AND MATERIALS: Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors. RESULTS: Univariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749. CONCLUSION: Our model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

Biallelic variants in ZFP36L2 cause female infertility characterised by recurrent preimplantation embryo arrest.

BACKGROUND: Recurrent preimplantation embryo developmental arrest (RPEA) is the most common cause of assisted reproductive technology treatment failure associated with identified genetic abnormalities. Variants in known maternal genes can only account for 20%-30% of these cases. The underlying genetic causes for the other affected individuals remain unknown. METHODS: Whole exome sequencing was performed for 100 independent infertile females that experienced RPEA. Functional characterisations of the identified candidate disease-causative variants were validated by Sanger sequencing, bioinformatics and in vitro functional analyses, and single-cell RNA sequencing of zygotes. RESULTS: Biallelic variants in ZFP36L2 were associated with RPEA and the recurrent variant (p.Ser308_Ser310del) prevented maternal mRNA decay in zygotes and HeLa cells. CONCLUSION: These findings emphasise the relevance of the relationship between maternal mRNA decay and human preimplantation embryo development and highlight a novel gene potentially responsible for RPEA, which may facilitate genetic diagnoses.

Crossover Sorption of C2 H2 /CO2 and C2 H6 /C2 H4 in Soft Porous Coordination Networks.

Porous sorbents are materials that are used for various applications, including storage and separation. Typically, the uptake of a single gas by a sorbent decreases with temperature, but the relative affinity for two similar gases does not change. However, in this study, we report a rare example of "crossover sorption," in which the uptake capacity and apparent affinity for two similar gases reverse at different temperatures. We synthesized two soft porous coordination polymers (PCPs), [Zn2 (L1)(L2)2 ]n (PCP-1) and [Zn2 (L1)(L3)2 ]n (PCP-2) (L1= 1,4-bis(4-pyridyl)benzene, L2=5-methyl-1,3-di(4-carboxyphenyl)benzene, and L3=5-methoxy-1,3-di(4-carboxyphenyl)benzene). These PCPs exhibits structural changes upon gas sorption and show the crossover sorption for both C2 H2 /CO2 and C2 H6 /C2 H4 , in which the apparent affinity reverse with temperature. We used in situ gas-loading single-crystal X-ray diffraction (SCXRD) analysis to reveal the guest inclusion structures of PCP-1 for C2 H2 , CO2 , C2 H6 , and C2 H4 gases at various temperatures. Interestingly, we observed three-step single-crystal to single-crystal (sc-sc) transformations with the different loading phases under these gases, providing insight into guest binding positions, nature of host-guest or guest-guest interactions, and their phase transformations upon exposure to these gases. Combining with theoretical investigation, we have fully elucidated the crossover sorption in the flexible coordination networks, which involves a reversal of apparent affinity and uptake of similar gases at different temperatures. We discovered that this behaviour can be explained by the delicate balance between guest binding and host-guest and guest-guest interactions.

Integrated Soft Porosity and Electrical Properties of Conductive-on-Insulating Metal-Organic Framework Nanocrystals.

A one-stone, two-bird method to integrate the soft porosity and electrical properties of distinct metal-organic frameworks (MOFs) into a single material involves the design of conductive-on-insulating MOF (cMOF-on-iMOF) heterostructures that allow for direct electrical control. Herein, we report the synthesis of cMOF-on-iMOF heterostructures using a seeded layer-by-layer method, in which the sorptive iMOF core is combined with chemiresistive cMOF shells. The resulting cMOF-on-iMOF heterostructures exhibit enhanced selective sorption of CO2 compared to the pristine iMOF (298 K, 1 bar, S CO 2 / H 2 ${{_{{\rm CO}{_{2}}/{\rm H}{_{2}}}}}$ from 15.4 of ZIF-7 to 43.2-152.8). This enhancement is attributed to the porous interface formed by the hybridization of both frameworks at the molecular level. Furthermore, owing to the flexible structure of the iMOF core, the cMOF-on-iMOF heterostructures with semiconductive soft porous interfaces demonstrated high flexibility in sensing and electrical "shape memory" toward acetone and CO2 . This behavior was observed through the guest-induced structural changes of the iMOF core, as revealed by the operando synchrotron grazing incidence wide-angle X-ray scattering measurements.

Multi-level semantic fusion network for Chinese medical named entity recognition.

Medical named entity recognition (MNER) is a fundamental component of understanding the unstructured medical texts in electronic health records, and it has received widespread attention in both academia and industry. However, the previous approaches of MNER do not make full use of hierarchical semantics from morphology to syntactic relationships like word dependency. Furthermore, extracting entities from Chinese medical texts is a more complex task because it usually contains for example homophones or pictophonetic characters. In this paper, we propose a multi-level semantic fusion network for Chinese medical named entity recognition, which fuses semantic information on morphology, character, word and syntactic level. We take radical as morphology semantic, pinyin and character dictionary as character semantic, word dictionary as word semantic, and these semantic features are fused by BiLSTM to get the contextualized representation. Then we use a graph neural network to model word dependency as syntactic semantic to enhance the contextualized representation. The experimental results show the effectiveness of the proposed model on two public datasets and robustness in real-world scenarios.

Structure-aware siamese graph neural networks for encounter-level patient similarity learning.

Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given patient and patient records in the database could contribute to clinical references for diagnosis and medication. The sparsity of underlying relationships between patients poses difficulties for similarity learning, which becomes more challenging when considering real-world Electronic Health Records (EHRs) with a large number of missing values. In the paper, we organize EHRs as a graph and propose a novel deep learning framework, Structure-aware Siamese Graph neural Networks (SSGNet), to perform robust encounter-level patient similarity learning while capturing the intrinsic graph structure and mitigating the influence from missing values. The proposed SSGNet regards each patient encounter as a node, and learns the node embeddings and the similarity between nodes simultaneously via Graph Neural Networks (GNNs) with siamese architecture. Further, SSGNet employs a low-rank and contrastive objective to optimize the structure of the patient graph and enhance model capacity. The extensive experiments were conducted on two publicly available datasets and a real-world dataset regarding IgA nephropathy from Peking University First Hospital, in comparison with multiple baseline and state-of-the-art methods. The significant improvement in Accuracy, Precision, Recall and F1 score on the patient encounter pairwise similarity classification task demonstrates the superiority of SSGNet. The mean average precision (mAP) of SSGNet on the similar encounter retrieval task is also better than other competitors. Furthermore, SSGNet's stable similarity classification accuracies at different missing rates of data validate the effectiveness and robustness of our proposal.

Enabling Real-Time Quality-of-Service and Fine-Grained Aggregation for Wireless TSN.

Wireless Time-Sensitive Networking (WTSN) has emerged as a promising technology for Industrial Internet of Things (IIoT) applications. To meet the latency requirements of WTSN, wireless local area network (WLAN) such as IEEE 802.11 protocol with the time division multiple access (TDMA) mechanism is shown to be a practical solution. In this paper, we propose the RT-WiFiQA protocol with two novel schemes to improve the latency and reliability performance: real-time quality of service (RT-QoS) and fine-grained aggregation (FGA) for TDMA-based 802.11 systems. The RT-QoS is designed to guarantee the quality-of-service requirements of different traffic and to support the FGA mechanism. The FGA mechanism aggregates frames for different stations to reduce the physical layer transmission overhead. The trade-off between the reliability and FGA packet size is analyzed with numerical results. Specifically, we derive a critical threshold such that the FGA can achieve higher reliability when the aggregated packet size is smaller than the critical threshold. Otherwise, the non-aggregation scheme outperforms the FGA scheme. Extensive experiments are conducted on the commercial off-the-shelf 802.11 interface. The experiment results show that compared with the existing TDMA-based 802.11 system, the developed RT-WiFiQA protocol can achieve deterministic bounded real-time latency and greatly improves the reliability performance.

Expanding the genetic and phenotypic spectrum of the subcortical maternal complex genes in recurrent preimplantation embryonic arrest.

The subcortical maternal complex (SCMC) is an oocyte-to-embryo-specific maternal functional module. Some variants of SCMC genes that contribute to preimplantation embryonic arrest have been identified. However, more novel variants should be identified to broaden the genetic and phenotypic spectrum of SCMC genes and establish their roles in embryonic development. We identified 13 novel variants in the SCMC genes, TLE6, NLRP5, NLRP2, and PADI6, from 10 of a total of 50 infertile females with recurrent preimplantation embryonic arrest. Six variants in TLE6 were found in five patients with embryonic arrest, accompanied by direct cleavage and severe fragmentation at the cleavage stage. Three patients carried NLRP5 variants, and one patient each who carried NLRP2 and PADI6 variants had subsequent poor or failed fertilization and cleavage arrest with a relatively lower ratio of severely fragmented embryos. Our findings expand the genetic and phenotypic spectrum of SCMC genes associated with human embryogenesis and might help lay the foundation for the genetic diagnosis of female infertility.

Increased Use of Complementary and Alternative Therapies for Back Pain Following Statewide Medicaid Coverage Changes in Oregon.

BACKGROUND: In 2016, Oregon introduced a policy to improve back pain treatment among Medicaid enrollees by expanding benefits for evidence-based complementary and alternative medical (CAM) services and establishing opioid prescribing restrictions. OBJECTIVE: To examine changes in CAM utilization following the policy and variations in utilization across patient populations. DESIGN: A retrospective study of Oregon Medicaid claims data, examining CAM therapy utilization by back pain patients pre- vs post-policy. We used an interrupted time series analysis to evaluate changes in CAM use and examined the association between patient characteristics and CAM use post-policy using linear regression models. PARTICIPANTS: Adult Medicaid patients with back pain. INTERVENTION: The Oregon Medicaid back pain policy, administered through Coordinated Care Organizations (CCOs). MAIN MEASURES: Use of CAM services. KEY RESULTS: Use of any CAM service increased from 7.9% (95% CI 7.6-8.2%) prior to the policy to 30.9% (95% CI 30.4-31.3%) after the policy. Acupuncture increased from 0.3 to 5.6%, chiropractic from 0.3 to 11.1%, massage from 1.6 to 14.8%, PT/OT from 6.0 to 17.7%, and osteopathic from 1.4 to 1.9%. Interrupted time series showed an overall increase in proportion of back pain patients who used CAM service following the policy. Among those who accessed CAM, the policy did not appear to increase the number of services used. In the post period, CAM services were accessed more often by female and older enrollees and urban populations. Black, American Indian/Alaska Native, and Hispanic enrollees were less likely to access CAM services; for Black enrollees, this was true for all types of services. CONCLUSIONS: CAM service utilization increased among back pain patients following implementation of Oregon's policy. There was significant heterogeneity in uptake across service types, CCOs, and patient subgroups. Policymakers should consider implementation factors that might limit impact and perpetuate health disparities.

8a, a New Acridine Antiproliferative and Pro-Apoptotic Agent Targeting HDAC1/DNMT1.

Epigenetic therapy using histone deacetylase (HDAC) inhibitors has become an attractive project in new drug development. However, DNA methylation and histone acetylation are important epigenetic ways to regulate the occurrence and development of leukemia. Given previous studies, N-(2-aminophenyl)benzamide acridine (8a), as a histone deacetylase 1 (HDAC1) inhibitor, induces apoptosis and shows significant anti-proliferative activity against histiocytic lymphoma U937 cells. HDAC1 plays a role in the nucleus, which we confirmed by finding that 8a entered the nucleus. Subsequently, we verified that 8a mainly passes through the endogenous (mitochondrial) pathway to induce cell apoptosis. From the protein interaction data, we found that 8a also affected the expression of DNA methyltransferase 1 (DNMT1). Therefore, an experiment was performed to assess the binding of 8a to DNMT1 at the molecular and cellular levels. We found that the binding strength of 8a to DNMT1 enhanced in a dose-dependent manner. Additionally, 8a inhibits the expression of DNMT1 mRNA and its protein. These findings suggested that the anti-proliferative and pro-apoptotic activities of 8a against leukemia cells were achieved by targeting HDAC1 and DNMT1.

Host-Guest Interaction Modulation in Porous Coordination Polymers for Inverse Selective CO2 /C2 H2 Separation.

Controlling gas sorption by simple pore modification is important in molecular recognition and industrial separation processes. In particular, it is challenging to realize the inverse selectivity, which reduces the adsorption of a high-affinity gas and increases the adsorption of a low-affinity gas. Herein, an "opposite action" strategy is demonstrated for boosting CO2 /C2 H2 selectivity in porous coordination polymers (PCPs). A precise steric design of channel pores using an amino group as an additional interacting site enabled the synergetic increase in CO2 adsorption while suppressing the C2 H2 adsorption. Based on this strategy, two new ultramicroporous PCP physisorbents that are isostructural were synthesised. They exhibited the highest CO2 uptake and CO2 /C2 H2 volume uptake ratio at 298 K. Origin of this specific selectivity was verified by detailed density functional theory calculations. The breakthrough separation performances with remarkable stability and recyclability of both the PCPs render them relevant materials for C2 H2 purification from CO2 /C2 H2 mixtures.