PheMIME: an interactive web app and knowledge base for phenome-wide, multi-institutional multimorbidity analysis.

OBJECTIVES: To address the need for interactive visualization tools and databases in characterizing multimorbidity patterns across different populations, we developed the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME). This tool leverages three large-scale EHR systems to facilitate efficient analysis and visualization of disease multimorbidity, aiming to reveal both robust and novel disease associations that are consistent across different systems and to provide insight for enhancing personalized healthcare strategies. MATERIALS AND METHODS: PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities, utilizing data from Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. It offers interactive and multifaceted visualizations for exploring multimorbidity. Incorporating an enhanced version of associationSubgraphs, PheMIME also enables dynamic analysis and inference of disease clusters, promoting the discovery of complex multimorbidity patterns. A case study on schizophrenia demonstrates its capability for generating interactive visualizations of multimorbidity networks within and across multiple systems. Additionally, PheMIME supports diverse multimorbidity-based discoveries, detailed further in online case studies. RESULTS: The PheMIME is accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial and multiple case studies for demonstration are available at https://prod.tbilab.org/PheMIME_supplementary_materials/. The source code can be downloaded from https://github.com/tbilab/PheMIME. DISCUSSION: PheMIME represents a significant advancement in medical informatics, offering an efficient solution for accessing, analyzing, and interpreting the complex and noisy real-world patient data in electronic health records. CONCLUSION: PheMIME provides an extensive multimorbidity knowledge base that consolidates data from three EHR systems, and it is a novel interactive tool designed to analyze and visualize multimorbidities across multiple EHR datasets. It stands out as the first of its kind to offer extensive multimorbidity knowledge integration with substantial support for efficient online analysis and interactive visualization.

Safety of embryo cryopreservation: insights from mid-term placental transcriptional changes.

BACKGROUND: In recent years, with benefits from the continuous improvement of clinical technology and the advantage of fertility preservation, the application of embryo cryopreservation has been growing rapidly worldwide. However, amidst this growth, concerns about its safety persist. Numerous studies have highlighted the elevated risk of perinatal complications linked to frozen embryo transfer (FET), such as large for gestational age (LGA) and hypertensive disorders during pregnancy. Thus, it is imperative to explore the potential risk of embryo cryopreservation and its related mechanisms. METHODS: Given the strict ethical constraints on clinical samples, we employed mouse models in this study. Three experimental groups were established: the naturally conceived (NC) group, the fresh embryo transfer (Fresh-ET) group, and the FET group. Blastocyst formation rates and implantation rates were calculated post-embryo cryopreservation. The impact of FET on fetal growth was evaluated upon fetal and placental weight. Placental RNA-seq was conducted, encompassing comprehensive analyses of various comparisons (Fresh-ET vs. NC, FET vs. NC, and FET vs. Fresh-ET). RESULTS: Reduced rates of blastocyst formation and implantation were observed post-embryo cryopreservation. Fresh-ET resulted in a significant decrease in fetal weight compared to NC group, whereas FET reversed this decline. RNA-seq analysis indicated that the majority of the expression changes in FET were inherited from Fresh-ET, and alterations solely attributed to embryo cryopreservation were moderate. Unexpectedly, certain genes that showed alterations in Fresh-ET tended to be restored in FET. Further analysis suggested that this regression may underlie the improvement of fetal growth restriction in FET. The expression of imprinted genes was disrupted in both FET and Fresh-ET groups. CONCLUSION: Based on our experimental data on mouse models, the impact of embryo cryopreservation is less pronounced than other in vitro manipulations in Fresh-ET. However, the impairment of the embryonic developmental potential and the gene alterations in placenta still suggested it to be a risky operation.

YEATS domain-containing protein GAS41 regulates nuclear shape by working in concert with BRD2 and the mediator complex in colorectal cancer.

The maintenance of nuclear shape is essential for cellular homeostasis and disruptions in this process have been linked to various pathological conditions, including cancer, laminopathies, and aging. Despite the significance of nuclear shape, the precise molecular mechanisms controlling it are not fully understood. In this study, we have identified the YEATS domain-containing protein 4 (GAS41) as a previously unidentified factor involved in regulating nuclear morphology. Genetic ablation of GAS41 in colorectal cancer cells resulted in significant abnormalities in nuclear shape and inhibited cancer cell proliferation both in vitro and in vivo. Restoration experiments revealed that wild-type GAS41, but not a YEATS domain mutant devoid of histone H3 lysine 27 acetylation or crotonylation (H3K27ac/cr) binding, rescued the aberrant nuclear phenotypes in GAS41-deficient cells, highlighting the importance of GAS41's binding to H3K27ac/cr in nuclear shape regulation. Further experiments showed that GAS41 interacts with H3K27ac/cr to regulate the expression of key nuclear shape regulators, including LMNB1, LMNB2, SYNE4, and LEMD2. Mechanistically, GAS41 recruited BRD2 and the Mediator complex to gene loci of these regulators, promoting their transcriptional activation. Disruption of GAS41-H3K27ac/cr binding caused BRD2, MED14 and MED23 to dissociate from gene loci, leading to nuclear shape abnormalities. Overall, our findings demonstrate that GAS41 collaborates with BRD2 and the Mediator complex to control the expression of crucial nuclear shape regulators.

Associations between maternal early pregnancy depression and longitudinal fetal growth.

BACKGROUND: The impacts of maternal depression during mid-to-late pregnancy on fetal growth have been extensively investigated. However, the association between maternal depression during early pregnancy and fetal intrauterine growth are less clear. METHODS: A prospective study comprised 23,465 eligible pregnant women and their offspring was conducted at a hospital-based center in Shanghai. Prenatal depression was assessed used using Patient Health Questionnaire (PHQ-9) before 14 gestational weeks. Differences in fetal growth trajectory of different maternal depressive statuses during three periods (16-23, 24-31, and 32-41 gestational weeks) were compared using a multilevel model with fractional polynomials. RESULTS: Women with depressive symptoms during early pregnancy had higher longitudinal fetal trajectories, with an estimated increase in fetal weight (ß = 0.33; 95 % CI, 0.06-0.61), compared to those without depressive symptoms. Increases in fetal abdominal circumference among women with depressive symptoms were observed before 23 gestational weeks. Offspring born to mothers with early pregnancy depression had a significantly higher birth weight of 14.13 g (95 % CI, 1.33-27.81 g) and an increased risk of severe large size for gestational age (adjusted odds ratio [aOR], 1.64; 95 % CI, 1.32-2.04) and macrosomia (aOR, 1.21; 95 % CI, 1.02-1.43). LIMITATIONS: Self-rated scale was used to assess depressive symptoms rather than clinical diagnosis. And Long-term effects of early pregnancy depression on offspring were not explored. CONCLUSIONS: The study revealed an association between maternal depression during early pregnancy and increased fetal biometrics, higher birth weight, and an elevated risk of severe large size for gestational age and macrosomia.

In situ imaging of intracellular miRNAs in tumour cells by branched hybridisation chain reaction.

The ability to visualise microRNA in situ is crucial for studying microRNAs, their microRNA-associated biological functions and disease diagnosis. Traditional fluorescence in situ hybridisation methods based on paraformaldehyde fixation of microRNAs suffer from release of microRNAs from cells, which limits the sensitivity of in situ hybridisation, making them unsuitable for the detection of small, low-abundance microRNAs. To reduce the loss, microRNAs were covalently cross-linked to proteins within cells by combining EDC and paraformaldehyde, and the target microRNA was used as the initiator chain for a branched hybridisation chain reaction to detect microRNA expression levels in situ. A simplified branched hybridisation chain reaction can be realised by coupling two hybridisation chain reaction circuits with a hairpin linker. Upon forming the primary hybridisation chain reaction product with extended sequence, this sequence reacts with the linker hairpin H3 to release the initiator sequence, resulting in the formation of numerous dendritic branched hybridisation chain reaction products. Imaging results show that this technique can detect microRNAs with high sensitivity and selectivity at both the single-cell and single-molecule levels. Compared with the traditional fluorescence in situ hybridisation technique, this method greatly improves the sensitivity and image resolution of in situ imaging detection. Therefore, we believe that the target-initiated branched hybridisation chain reaction based in situ detection method provides a reliable assay platform for analysing disease-related microRNA expression.

Study of transient absorption spectroscopy of a D-π-A structure aggregation-induced emission luminogen and its photodynamic therapy application.

Photodynamic therapy (PDT) represents an emerging and noninvasive modality that has gained clinical approval for the treatment of cancers, leveraging photosensitizers for optimal therapeutic efficacy. In this study, we synthesized a photosensitizer (denoted as DTCSPP) exhibiting a donor-π-acceptor (D-π-A) structural motif. The DTCSPP manifests aggregation-induced emission (AIE) characteristics, along with good biocompatibility and mitochondrial targeting capabilities attributed to its intrinsic charge and D-π-A architecture. The excited-state intramolecular charge transfer of DTCSPP was systematically investigated in both solution and aggregate states using femtosecond transient absorption spectroscopy (fs-TA). The fs-TA results revealed that DTCSPP exhibited a more rapid and facile excited-state molecular motion in the solution state compared to the aggregate state, implying the predominance of nonradiative decay in its photophysical processes within the solution. Given its ability to simultaneously generate type I and type II reactive oxygen species and induce ferroptosis and autophagy in cancer cells, DTCSPP demonstrates effectiveness in PDT at both cellular and in vivo levels. This study contributes a comprehensive understanding of the excited-state intramolecular charge transfer dynamics of charged D-π-A type AIE photosensitizers, shedding light on their potential application in PDT. The multifaceted capabilities of DTCSPP underscore its promise in advancing the field of anticancer therapeutics, providing valuable insights for the identification of anticancer targets and the development of novel drugs.

A review of recent advances of piezoelectric poly-L-lactic acid for biomedical applications.

Poly-L-lactic acid (PLLA), recognized as a piezoelectric material, not only demonstrates exceptional piezoelectric properties but also exhibits commendable biocompatibility and biodegradability. These properties render PLLA highly promising for diverse applications, including sensors, wearable devices, biomedical engineering, and related domains. This review offers a comprehensive overview of the distinctive piezoelectric effect of PLLA-based material and delves into the latest advancements in its preparation strategies as a piezoelectric material. It further presents recent research progress in PLLA-based piezoelectric materials, particularly in the realms of health monitoring, skin repair, nerve regeneration, and tissue repair. The discourse extends to providing insights into potential future trajectories for the development of PLLA-based piezoelectric materials.

Probing action potentials of single beating cardiomyocytes using atomic force microscopy.

This paper presents a method for using atomic force microscopy to probe action potentials of single beating cardiomyocytes at the nanoscale. In this work, the conductive tip of an atomic force microscope (AFM) was used as a nanoelectrode to record the action potentials of self-beating cardiomyocytes in both the non-constant force contact mode and the constant force contact mode. An electrical model of a tip-cell interface was developed and the indentation force effect on the seal of an AFM conductive tip-cell membrane was theoretically analyzed. The force feedback of AFM allowed for the precise control of tip-cell contact, and enabled reliable measurements. The feasibility of simultaneously recording the action potentials and force information during the contraction of the same beating cardiomyocyte was studied. Furthermore, the AFM tip electrode was used to probe the differences of action potentials using different drugs. This method provides a way at the nanoscale for electrophysiological studies on single beating cardiomyocytes, neurons, and ion channels embedded within the cell membrane in relation to disease states, pharmaceutical drug testing and screening.

Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia.

Despite genome-wide association studies of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci1-6, the underlying disease mechanisms remain largely unknown. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Leveraging our approach for identifying functional GWAS risk variants showing allele-specific open chromatin (ASoC)7, we systematically identified putative causal LOAD risk variants in human induced pluripotent stem cells (iPSC)-derived neurons, astrocytes, and microglia (MG) and linked PICALM risk allele to a previously unappreciated MG-specific role of PICALM in lipid droplet (LD) accumulation. ASoC mapping uncovered functional risk variants for 26 LOAD risk loci, mostly MG-specific. At the MG-specific PICALM locus, the LOAD risk allele of rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aß) and myelin debris. Interestingly, MG with PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of MG further established a causal link between the reduced PICALM expression, LD accumulation, and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia for the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing novel clinical interventions.

Observation of Bose-Einstein condensation of dipolar molecules.

Ensembles of particles governed by quantum mechanical laws exhibit intriguing emergent behaviour. Atomic quantum gases1,2, liquid helium3,4 and electrons in quantum materials5-7 all exhibit distinct properties because of their composition and interactions. Quantum degenerate samples of ultracold dipolar molecules promise the realization of new phases of matter and new avenues for quantum simulation8 and quantum computation9. However, rapid losses10, even when reduced through collisional shielding techniques11-13, have so far prevented evaporative cooling to a Bose-Einstein condensate (BEC). Here we report on the realization of a BEC of dipolar molecules. By strongly suppressing two- and three-body losses via enhanced collisional shielding, we evaporatively cool sodium-caesium molecules to quantum degeneracy and cross the phase transition to a BEC. The BEC reveals itself by a bimodal distribution when the phase-space density exceeds 1. BECs with a condensate fraction of 60(10)% and a temperature of 6(2) nK are created and found to be stable with a lifetime close to 2 s. This work opens the door to the exploration of dipolar quantum matter in regimes that have been inaccessible so far, promising the creation of exotic dipolar droplets14, self-organized crystal phases15 and dipolar spin liquids in optical lattices16.

Aggregative Luminescence from CsPbBr3 Perovskite Precursors.

Understanding the properties of the precursor can provide deeper insight into the crystallization and nucleation mechanisms of perovskites, which is vital for the solution-process device performance. Herein, we conducted a detailed investigation into the photophysics properties of CsPbBr3 precursors in a broad concentration and various solvents. The precursor transformed from the solution state into the colloidal state and exhibited aggregation-induced emission character as the concentration increased. The aggregative luminescence from the precursors originates from the polybromide plumbous that is formed through the coordination of solvent molecules to the lead metal center. Two adducts with monodentate (PbBr2 ⋅ solvent) and bidentate (PbBr2 ⋅ 2solvent) ligands can be obtained, accompanied by emission with photoluminescence at 610 and 565 nm, respectively. Furthermore, the aggregative luminescence intensity and color could be regulated by changing the solvent and precursor ratio. Besides, we discussed the difference between the molecular aggregate in the organic system and the ionic aggregate in the inorganic system: the ionic aggregate is composed of solvated ions rather than individual molecules as in organic systems, which could possess properties that ions do not have. The fluorescence that is sensitive to Pb2+ coordination reported here could be applied to screen perovskite additives and judge the precursor aging.

Overcome the Limitation of Phenome-Wide Association Studies (PheWAS): Extension of PheWAS to Efficient and Robust Large-Scale ICD Codes Analysis.

The Phenome-wide association studies (PheWAS) have become widely used for efficient, high-throughput evaluation of relationship between a genetic factor and a large number of disease phenotypes, typically extracted from a DNA biobank linked with electronic medical records (EMR). Phecodes, billing code-derived disease case-control status, are usually used as outcome variables in PheWAS and logistic regression has been the standard choice of analysis method. Since the clinical diagnoses in EMR are often inaccurate with errors which can lead to biases in the odds ratio estimates, much effort has been put to accurately define the cases and controls to ensure an accurate analysis. Specifically in order to correctly classify controls in the population, an exclusion criteria list for each Phecode was manually compiled to obtain unbiased odds ratios. However, the accuracy of the list cannot be guaranteed without extensive data curation process. The costly curation process limits the efficiency of large-scale analyses that take full advantage of all structured phenotypic information available in EMR. Here, we proposed to estimate relative risks (RR) instead. We first demonstrated the desired nature of RR that overcomes the inaccuracy in the controls via theoretical formula. With simulation and real data application, we further confirmed that RR is unbiased without compiling exclusion criteria lists. With RR as estimates, we are able to efficiently extend PheWAS to a larger-scale, phenome construction agnostic analysis of phenotypes, using ICD 9/10 codes, which preserve much more disease-related clinical information than Phecodes.

The Brassinosteroid Receptor StBRI1 Promotes Tuber Development by Enhancing Plasma Membrane H+-ATPase Activity in Potato.

The brassinosteroid (BR) receptor BRASSINOSTEROID-INSENSITIVE 1 (BRI1) plays a critical role in plant growth and development. Although much is known about how BR signaling regulates growth and development in many crop species, the role of StBRI1 in regulating potato (Solanum tuberosum) tuber development is not well understood. To address this question, a series of comprehensive genetic and biochemical methods were applied in this investigation. It was determined that StBRI1 and Solanum tuberosum PLASMA MEMBRANE (PM) PROTON ATPASE2 (PHA2), a PM-localized proton ATPase, play important roles in potato tuber development. The individual overexpression of StBRI1 and PHA2 led to a 22% and 25% increase in tuber yield per plant, respectively. Consistent with the genetic evidence, in vivo interaction analysis using double transgenic lines and PM H+-ATPase activity assays indicated that StBRI1 interacts with the C-terminus of PHA2, which restrains the intramolecular interaction of the PHA2 C-terminus with the PHA2 central loop to attenuate autoinhibition of PM H+-ATPase activity, resulting in increased PHA2 activity. Furthermore, the extent of PM H+-ATPase autoinhibition involving phosphorylation-dependent mechanisms corresponds to phosphorylation of the penultimate Thr residue (Thr-951) in PHA2. These results suggest that StBRI1 phosphorylates PHA2 and enhances its activity, which subsequently promotes tuber development. Altogether, our results uncover a BR-StBRI1-PHA2 module that regulates tuber development and suggest a prospective strategy for improving tuberous crop growth and increasing yield via the cell surface-based BR signaling pathway.

Investigation of the formation mechanism of the pepper starch-piperine complex.

In this study, a new carrier for loading piperine was prepared using pepper starch, and its interaction mechanism was investigated. The porous pepper starch-piperine complex (PPS-PIP) showed higher loading efficiency (76.15 %) compared to the porous corn starch-piperine complex (PCS-PIP (52.34 %)). This may be ascribed to the hemispherical shell structure of porous pepper starch (PPS) compared to the porous structure of porous corn starch (PCS) based on the SEM result. PPS-PIP had smaller particle size (10.53 µm), higher relative crystallinity (38.95 %), and better thermal stability (87.45 °C) than PCS-PIP (17.37 µm, 32.17 %, 74.35 °C). Fourier transform infrared spectroscopy (FTIR) results implied that piperine not only forms a complex with amylose but may also be physically present in porous starch. This was demonstrated by the short-range order and X-ray type. Molecular dynamics simulations confirmed that hydrogen bonding is the primary interaction between amylose and piperine. Besides the formation of the amylose-piperine complex, some of the piperine is also present in physical form.

Integrating Electronic Health Records and Polygenic Risk to Identify Genetically Unrelated Comorbidities of Schizophrenia That May Be Modifiable.

Background: Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations. Methods: Phenome-wide comorbidity was calculated from electronic health records of 250,000 patients across 2 independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham); associations with schizophrenia polygenic risk scores were calculated across the same phenotypes in linked biobanks. Results: Schizophrenia comorbidity was significantly correlated across institutions (r = 0.85), and the 77 identified comorbidities were consistent with prior literature. Overall, comorbidity and polygenic risk score associations were significantly correlated (r = 0.55, p = 1.29 × 10-118). However, directly testing for the absence of genetic effects identified 36 comorbidities that had significantly equivalent schizophrenia polygenic risk score distributions between cases and controls. This set included phenotypes known to be consequences of antipsychotic medications (e.g., movement disorders) or of the disease such as reduced hygiene (e.g., diseases of the nail), thereby validating the approach. It also highlighted phenotypes with less clear causal relationships and minimal genetic effects such as tobacco use disorder and diabetes. Conclusions: This work demonstrates the consistency and robustness of electronic health record-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies known and novel comorbidities with an absence of shared genetic risk, indicating other causes that may be modifiable and where further study of causal pathways could improve outcomes for patients.

Patients with schizophrenia have many co-occurring diseases that contribute substantially to premature mortality of 10 to 20 years. Conditions that are comorbid but lack shared genetic risk with schizophrenia are likely to have causes that are more modifiable. Here, we calculated comorbidity from electronic health records from 2 independent health care institutions and associations with schizophrenia polygenic risk scores across the same phenotypes in linked biobanks. We identified known and novel diseases comorbid with schizophrenia, thereby validating our approach.

Interoperability of phenome-wide multimorbidity patterns: a comparative study of two large-scale EHR systems.

Background: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administrative purposes raise questions about the consistency and reproducibility of EHR-based multimorbidity research. Methods: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph. We assessed the consistency of the multimorbidity networks within and between two major EHR systems at local (nodes and edges), meso (neighboring patterns), and global (network statistics) scales. We present case studies to identify disease clusters and uncover clinically interpretable disease relationships. We provide an interactive web tool and a knowledge base combining data from multiple sources for online multimorbidity analysis. Findings: Analyzing data from 500,000 patients across Vanderbilt University Medical Center and Mass General Brigham health systems, we observed a strong correlation in disease frequencies (Kendall's τ = 0.643) and comorbidity strengths (Pearson ρ = 0.79). Consistent network statistics across EHRs suggest similar structures of multimorbidity networks at various scales. Comorbidity strengths and similarities of multimorbidity connection patterns align with the disease genetic correlations. Graph-theoretic analyses revealed a consistent core-periphery structure, implying efficient network clustering through threshold graph construction. Using hydronephrosis as a case study, we demonstrated the network's ability to uncover clinically relevant disease relationships and provide novel insights. Interpretation: Our findings demonstrate the robustness of large-scale EHR data for studying phenome-wide multimorbidities. The alignment of multimorbidity patterns with genetic data suggests the potential utility for uncovering shared biology of diseases. The consistent core-periphery structure offers analytical insights to discover complex disease interactions. This work also sets the stage for advanced disease modeling, with implications for precision medicine. Funding: VUMC Biostatistics Development Award, the National Institutes of Health, and the VA CSRD.

Enhancing therapeutic efficacy in luminal androgen receptor triple-negative breast cancer: exploring chidamide and enzalutamide as a promising combination strategy.

Extensive exploration of the molecular subtypes of triple-negative breast cancer (TNBC) is critical for advancing precision medicine. Notably, the luminal androgen receptor (LAR) subtype has attracted attention for targeted treatment combining androgen receptor antagonists and CDK4/6 inhibitors. Unfortunately, this strategy has proven to be of limited efficacy, highlighting the need for further optimization. Using our center's comprehensive multiomics dataset (n = 465), we identified novel therapeutic targets and evaluated their efficacy through multiple models, including in vitro LAR cell lines, in vivo cell-derived allograft models and ex vivo patient-derived organoids. Moreover, we conducted flow cytometry and RNA-seq analysis to unveil potential mechanisms underlying the regulation of tumor progression by these therapeutic strategies. LAR breast cancer cells exhibited sensitivity to chidamide and enzalutamide individually, with a drug combination assay revealing their synergistic effect. Crucially, this synergistic effect was verified through in vivo allograft models and patient-derived organoids. Furthermore, transcriptomic analysis demonstrated that the combination therapeutic strategy could inhibit tumor progression by regulating metabolism and autophagy. This study confirmed that the combination of histone deacetylase (HDAC) inhibitors and androgen receptor (AR) antagonists possessed greater therapeutic efficacy than monotherapy in LAR TNBC. This finding significantly bolsters the theoretical basis for the clinical translation of this combination therapy and provides an innovative strategy for the targeted treatment of LAR TNBC.

Scaled and Efficient Derivation of Loss of Function Alleles in Risk Genes for Neurodevelopmental and Psychiatric Disorders in Human iPSC.

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPD) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, here we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop-codons (iSTOP) that lead to mRNA nonsense-mediated-decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 NPD genes. Using RNAseq, we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Interestingly, for three schizophrenia risk genes (SETD1A, TRIO, CUL1), despite the high efficiency of base editing, we only obtained heterozygous LoF alleles, suggesting their essential roles for cell growth. We replicated the reported neural phenotypes of SHANK3-haploinsufficiency and found CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.

Turning Non-Emissive Schiff Bases Into Aggregate Emitters.

Schiff bases are a crucial component in various functional materials but often exhibit non-emissive behavior which significantly limits their potential applications as luminescent materials. However, traditional approaches to convert them into aggregate emitters often require intricate molecular design, tedious synthesis, and significant time and resource consumption. Herein, we present a cocrystallization-induced emission strategy that can transform non-emissive (hetero)aryl-substituted Schiff bases into green-yellow to yellow aggregate emitters via even simple grinding of a mixture of Schiff bases and 1,2,4,5-tetracyanobenzene (TCB) mixtures. The combined experimental and theoretical analysis revealed that the cocrystallization inhibits the C=N isomerization and promotes face-to-face π-π interaction, which restricts access to both the dark state and canonical intersection to ultimately induce emission. Furthermore, the induced emission enables the observation of solid-state molecular diffusion through fluorescence signals, advancing white light emission diodes, and notably, solution-processed organic light-emitting diodes based on cocrystal for the first time. This study not only highlights the potential of developing new C=N structural motifs for AIEgens but also could boost advancements in related structure motifs like C=C and N=N.

The number of test organisms might influence the toxicity evaluation of hydrophobic micropollutants.

Evaluating the toxicity of micropollutants forms the basis for understanding their potential risks to the ecosystem and/or human health. To accurately evaluate the toxicity of micropollutants in toxicity tests, many factors have been carefully considered, while the impact of the number of test organisms on toxicity results has rarely been taken into account. In this study, the role of the organism number on the developmental toxicity of five micropollutants was investigated using embryos of the marine polychaete Platynereis dumerilii. The toxicity of hydrophobic micropollutants was found to decrease significantly with increasing the number of embryos used in the test. A quantitative model was developed to better describe how the number of embryos affected developmental toxicity. The model showed a satisfactory fit to the raw data in all scenarios tested. The intrinsic half-maximal effective concentration EC50,int was then determined using the model. For a given compound, the EC50,int was a stable parameter that did not depend on the number of test embryos and thus provided an indication of the intrinsic toxicity of the compounds tested. Compared with the EC50 values determined with the commonly used embryo number (around 120), the EC50,int values of all tested hydrophobic micropollutants were lower. The more hydrophobic the compounds tested, the more pronounced the reduction in toxicity. This suggested that hydrophobic micropollutants could be more toxic than reported in the literature. Some suggestions were also made to eliminate the effect of the number of organisms used in the toxicity evaluation.