Development and internal validation of a clinical prediction model for osteopenia in Chinese middle-aged and elderly men: a prospective cohort study.

BACKGROUND: Early identification of patients at risk of osteopenia is an essential step in reducing the population at risk for fractures. We aimed to develop and validate a prediction model for osteopenia in Chinese middle-aged and elderly men that provides individualized risk estimates. METHODS: In this prospective cohort study, 1109 patients who attend regular physical examinations in the Second Medical Centre of Chinese PLA General Hospital were enrolled from 2015.03 to 2015.09. The baseline risk factors included dietary habits, exercise habits, medical histories and medication records. Osteopenia during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Internal validation was conducted using bootstrapping to correct the optimism. The independent sample T-test analysis, Mann_Whitney U test, Chi-Square Test and multivariable Cox regression analysis were utilized to identify predictive factors for osteopenia in Chinese middle-aged and elderly men. A nomogram based on the seven variables was built for clinical use. Concordance index (C-index), receiver operating characteristic curve (ROC), decision curve analysis (DCA) and calibration curve were used to evaluate the efficiency of the nomogram. RESULTS: The risk factors included in the prediction model were bone mineral density at left femoral neck (LNBMD), hemoglobin (Hb), serum albumin (ALB), postprandial blood glucose (PBG), fatty liver disease (FLD), smoking and tea consumption. The C-index for the risk nomogram was 0.773 in the prediction model, which presented good refinement. The AUC of the risk nomogram at different time points ranged from 0.785 to 0.817, exhibiting good predictive ability and performance. In addition, the DCA showed that the nomogram had a good clinical application value. The nomogram calibration curve indicated that the prediction model was consistent. CONCLUSIONS: Our study provides a novel nomogram and a web calculator that can effectively predict the 7-year incidence risk of osteopenia in Chinese middle-aged and elderly men. It is convenient for clinicians to prevent fragility fractures in the male population.

Designing semiconductor materials and devices in the post-Moore era by tackling computational challenges with data-driven strategies.

In the post-Moore's law era, the progress of electronics relies on discovering superior semiconductor materials and optimizing device fabrication. Computational methods, augmented by emerging data-driven strategies, offer a promising alternative to the traditional trial-and-error approach. In this Perspective, we highlight data-driven computational frameworks for enhancing semiconductor discovery and device development by elaborating on their advances in exploring the materials design space, predicting semiconductor properties and optimizing device fabrication, with a concluding discussion on the challenges and opportunities in these areas.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study.

BACKGROUND: There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling. METHODS: A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening. RESULTS: At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%. CONCLUSIONS: The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Imaging Transcriptomics of the Brain for Schizophrenia.

Schizophrenia is a severe mental disorder with a neurodevelopmental origin. Although schizophrenia results from changes in the brain, the underlying biological mechanisms are unknown. Transcriptomics studies quantitative expression changes or qualitative changes of all genes and isoforms, providing a more meaningful biological insight. Magnetic resonance imaging (MRI) techniques play roles in revealing brain structure and function. We give a narrative focused review on the current transcriptome combined with MRI studies related to schizophrenia and summarize the research methodology and content of these studies to identify the research commonalities as well as the implications for future research, in an attempt to provide new insights into the mechanism, clinical diagnosis, and treatments of schizophrenia.

Second-harmonic generation in 2D moiré superlattices composed of bilayer transition metal dichalcogenides.

Moiré superlattices (MSLs) in twisted two-dimensional van der Waals materials feature twist-angle-dependent crystal symmetry and strong optical nonlinearities. By adjusting the twist angle in bilayer van der Waals materials, the second-harmonic generation (SHG) can be controlled. Here, we focus on exploring the electronic and SHG properties of MSLs in 2D bilayer transition metal dichalcogenides (TMDs) with different twist angles through first-principles calculations. We constructed MSL structures of five TMD materials, including three single-phase materials (MoS2, WS2, and MoSe2) and two heterojunctions (MoS2/MoSe2 and MoS2/WS2) with twist angles of 9.4°, 13.2°, 21.8°, 32.2°, and 42.1° without lattice mismatch. Our findings demonstrate a consistent variation in the SHG susceptibility among different TMD MSLs as a response to twist-angle changes. The underlying reason for the twist-angle dependence of SHG is that the twist angle regulates the interlayer coupling strength, affecting the optical band gap of MSLs and subsequently tuning the SHG susceptibility. Through a comparison of the static SHG susceptibility values, we identified the twist angle of 9.4° as the configuration that yields the highest SHG susceptibility (e.g. 358.5 pm V-1 for the 9.4° MoSe2 MSL). This value is even twice that of the monolayer (173.3 pm V-1 for monolayer MoSe2) and AA'-stacked bilayer structures (139.8 pm V-1 for AA' MoSe2). This high SHG susceptibility is attributed to the strong interlayer coupling in the 9.4° MSL, which enhances the valence band energy (contributed by the antibonding orbitals of chalcogen-pz and transition metal-dz2) and consequently leads to a small optical band gap, thus improving the optical transitions. The findings of this study provide a straightforward way to improve the SHG performance of bilayer TMDs and also throw light on the sensitive relationship between the twist angle, band structure and SHG properties of TMD MSLs.

Environmental regulation and high-quality agricultural development.

The key trend for future agricultural growth is efficient, green and sustainable high-quality development, and it is crucial to sort out the factors influencing high-quality agricultural development. OBJECTIVES: The purpose of this study is to dissect whether environmental regulation has a catalytic effect on quality rural development, through which paths it is driven and whether there is a threshold effect to be further clarified. METHOD: In this study, the panel data of 34 provinces in China from 2012 to 2018 are used, and 17 variables are used to construct an evaluation index system, covering four dimensions: agricultural endowment, agricultural output level, agricultural green degree and social sustainability. The high-quality development of agriculture is measured by entropy method. And further, using a baseline regression model and a mediating effects model, we empirically investigated the impact of environmental regulation on high-quality agricultural development and its mechanism of action, and empirically assessed the nonlinear effects of environmental regulation using a threshold regression model. RESULTS: Environmental control, as noted in the study, considerably assists in the establishment of high-quality agriculture; at the same time, large-scale land management plays a role in mitigating the influence of both. There is a single income threshold impact on rural households between high-quality agricultural growth and environmental regulation, and once that threshold is reached, the influence of high-quality agricultural growth grows. Contribution: According to the research findings, recommendations are made for the design of scientific environmental regulation policies, the establishment of a sound service system for large-scale rural land management, and the establishment of a stable mechanism for rural residents to sustain their income, in order to strengthen the effect of environmental regulation and realize high-quality agricultural growth in China. The marginal contribution of this paper is to enrich the study of the relationship between environmental regulation and high-quality agricultural development, which has theoretical and practical implications for promoting sustainable agricultural development.

Longitudinal real world correlation study of blood pressure and novel features of cerebral magnetic resonance angiography by artificial intelligence analysis on elderly cognitive impairment.

Objective: This study aims to investigate novel clinical risk factors for cognitive impairment (CI) in elderly. Methods: A total of 3221 patients (259 patients with CI and 2,962 subjects without CI) were recruited into this nested case-control study who underwent cerebral magnetic resonance angiography (MRA) from 2007 to 2021. All of the clinical data with MRA imaging were recorded followed by standardization processing blindly. The maximum stenosis score of the posterior circulatory artery, including the basilar artery, and bilateral posterior cerebral artery (PCA), was calculated by the cerebral MRA automatic quantitative analysis method. Logistic regression (LR) analysis was used to evaluate the relationship between risk factors and CI. Four machine learning approaches, including LR, decision tree (DT), random forest (RF), and support vector machine (SVM), employing 5-fold cross-validation were used to establish CI predictive models. Results: After matching with age and gender, 208 CI patients and 208 control subjects were finalized the follow-up (3.46 ± 3.19 years) with mean age at 84.47 ± 6.50 years old. Pulse pressure (PP) in first tertile (<58 mmHg) (OR 0.588, 95% confidence interval (CI): 0.362-0.955) was associated with a decreased risk for CI, and ≥50% stenosis of the left PCA (OR 2.854, 95% CI: 1.387-5.872) was associated with an increased risk for CI after adjusting for body mass index, myocardial infarction, and stroke history. Based on the means of various blood pressure (BP) parameters, the performance of the LR, DT, RF and SVM models accurately predicted CI (AUC 0.740, 0.786, 0.762, and 0.753, respectively) after adding the stenosis score of posterior circulatory artery. Conclusion: Elderly with low pulse differential pressure may have lower risk for cognitive impairment. The hybrid model combined with the stenosis score of posterior circulatory artery, clinical indicators, and the means of various BP parameters can effectively predict the risk of CI in elderly individuals.

Dual Targeting of MDM4 and FTH1 by MMRi71 for Induced Protein Degradation and p53-Independent Apoptosis in Leukemia Cells.

MDM2 and MDM4 are cancer drug targets validated in multiple models for p53-based cancer therapies. The RING domains of MDM2 and non-p53-binder MDM2 splice isoforms form RING domain heterodimer polyubiquitin E3 ligases with MDM4, which regulate p53 stability in vivo and promote tumorigenesis independent of p53. Despite the importance of the MDM2 RING domain in p53 regulation and cancer development, small molecule inhibitors targeting the E3 ligase activity of MDM2-MDM4 are poorly explored. Here, we describe the synthesis and characterization of quinolinol derivatives for the identification of analogs that are capable of targeting the MDM2-MDM4 heterodimer E3 ligase and inducing apoptosis in cells. The structure-activity-relationship (SAR) study identified structural moieties critical for the inhibitory effects toward MDM2-MDM4 E3 ligase, the targeted degradation of MDM4 and FTH1 in cells, and anti-proliferation activity. Lead optimization led to the development of compound MMRi71 with improved activity. In addition to accumulating p53 proteins in wt-p53 bearing cancer cells as expected of any MDM2 inhibitors, MMRi71 effectively kills p53-null leukemia cells, an activity that conventional MDM2-p53 disrupting inhibitors lack. This study provides a prototype structure for developing MDM4/FTH1 dual-targeting inhibitors as potential cancer therapeutics.

Small molecule MMRi62 targets MDM4 for degradation and induces leukemic cell apoptosis regardless of p53 status.

MDM2 and MDM4 proteins are key negative regulators of tumor suppressor p53. MDM2 and MDM4 interact via their RING domains and form a heterodimer polyubiquitin E3 ligase essential for p53 degradation. MDM4 also forms heterodimer E3 ligases with MDM2 isoforms that lack p53-binding domains, which regulate p53 and MDM4 stability. We are working to identify small-molecule inhibitors targeting the RING domain of MDM2-MDM4 (MMRi) that can inactivate the total oncogenic activity of MDM2-MDM4 heterodimers. Here, we describe the identification and characterization of MMRi62 as an MDM4-degrader and apoptosis inducer in leukemia cells. Biochemically, in our experiments, MMRi62 bound to preformed RING domain heterodimers altered the substrate preference toward MDM4 ubiquitination and promoted MDM2-dependent MDM4 degradation in cells. This MDM4-degrader activity of MMRi62 was found to be associated with potent apoptosis induction in leukemia cells. Interestingly, MMRi62 effectively induced apoptosis in p53 mutant, multidrug-resistant leukemia cells and patient samples in addition to p53 wild-type cells. In contrast, MMRi67 as a RING heterodimer disruptor and an enzymatic inhibitor of the MDM2-MDM4 E3 complex lacked MDM4-degrader activity and failed to induce apoptosis in these cells. In summary, this study identifies MMRi62 as a novel MDM2-MDM4-targeting agent and suggests that small molecules capable of promoting MDM4 degradation may be a viable new approach to killing leukemia cells bearing non-functional p53 by apoptosis.

Design of Organic-Inorganic Hybrid Heterostructured Semiconductors via High-Throughput Materials Screening for Optoelectronic Applications.

Organic-inorganic hybrid semiconductors, of which organometal halide perovskites are representative examples, have drawn significant research interest as promising candidates for next-generation optoelectronic applications. This interest is mainly ascribed to the emergent optoelectronic properties of the hybrid semiconductors that are distinct from those of their purely inorganic and organic counterparts as well as different material fabrication strategies and the other material (e.g., mechanical) properties that combine the advantages of both. Herein, we present a high-throughput first-principles material screening study of the hybrid heterostructured semiconductors (HHSs) that differ entirely from organometal halide perovskite hybrid ion-substituting semiconductors. HHSs crystallize as superlattice structures composed of inorganic tetrahedrally coordinated semiconductor sublayers and organic sublayers made of bidentate chain-like molecules. By changing the composition (e.g., IV, III-V, II-VI, I-III-VI2 semiconductor) and polymorph (e.g., wurtzite and zinc-blende) of the inorganic components, the type of organic molecules (e.g., ethylenediamine, ethylene glycol, and ethanedithiol), and the thickness of the composing layers across 234 candidate HHSs, we investigated their thermodynamic, electronic structure, and optoelectronic properties. Thermodynamic stability analysis indicates the existence of 96 stable HHSs beyond the ZnTe/ZnSe-based ones synthesized experimentally. The electronic structure and optoelectronic properties of HHSs can be modulated over a wide range by manipulating their structural variants. A machine learning approach was further applied to the high-throughput calculated data to identify the critical descriptors determining thermodynamic stability and electronic band gap. Our results indicate promising prospects and provide valuable guidance for the rational design of organic-inorganic hybrid heterostructured semiconductors for potential optoelectronic applications.

Electronic property modulation in two-dimensional lateral superlattices of monolayer transition metal dichalcogenides.

Fabricating lateral heterostructures (HSs) and superlattices (SLs) provides a unique degree of freedom for modulating the physical properties of two-dimensional (2D) materials by varying the chemical component, geometric size and interface structure in the ultra-thin atomic thickness limit. While a variety of 2D lateral HSs/SLs have been synthesized, especially for transition metal dichalcogenides (TMDs), how such structures affect quantitatively the physical properties of 2D materials has not yet been established. We herein explore electronic property modulation in 2D lateral SLs of monolayer TMDs through first-principles high-throughput calculations. The dependence of the electronic structure, bandgap, carrier effective masses, charge density overlap on chemical components, interface type, and sub-lattice size of lateral TMD-SLs are investigated. We find that by comparison with their random alloy counterparts, the lateral TMD-SLs exhibit generally type-II band alignment, a wider range of bandgap tunability, larger carrier effective masses, and stronger electron-hole charge separation tendency. The bandgap variation with a sub-lattice size shows larger bowing parameters for the SLs with heterogeneous anions, by comparison with the homogeneous anion cases. A similar behavior is observed for the SLs with an armchair-type interface, by comparison with the zigzag-type interface cases. Further analyses reveal that the underlying physical mechanism can be attributed to the synergistic interplay among the band offset of sub-lattices, quantum confinement effect, and existing internal strain.

Thermal Shock Fabrication of Ion-Stabilized Perovskite and Solar Cells.

A highly crystalline tempered-glass-like perovskite grain structure with compressed surface lattice realized by a thermal-shocking fabrication is shown. The strained perovskite grain structure is stabilized by Cl- -reinforcing surface lattice and shows enhanced bonding energy and ionic activation temperature, which contributes to hysteresis-free operation of perovskite solar cells (PSCs) at much higher temperature up to 363 K in thermal-shocking-processed MAPbClx I3- x (T-MPI). The PSCs can be fabricated by a high-speed fully air process without post-annealing based on the scalable bar-coating technique. Both high efficiency and stability are achieved in T-MPI PSC with a power conversion efficiency (PCE) up to 22.99% and long-term operational stability with T80 lifetime exceeding 4000 h.

Entropy-Driven Stabilization of Multielement Halide Double-Perovskite Alloys.

Currently, a major obstacle restricting the commercial application of halide perovskites is their low thermodynamic stability. Herein, inspired by the high-stability high-entropy alloys, we theoretically investigated a variety of multielement double-perovskite alloys. First-principles calculations show that the entropy contribution to Gibbs free energy, which offsets the positive enthalpy contribution by up to 35 meV/f.u., can significantly enhance the material stability of double-perovskite alloys. We found that the electronic properties of bandgaps (1.04-2.21 eV) and carrier effective masses (0.34 to greater than 2 m0) of the multielement double-perovskite alloys can be tuned over a wide range. Meanwhile, the parity-forbidden condition of optical transitions in the Cs2AgInCl6 perovskite can be broken because of the lower symmetry of the configurational disorder, leading to enhanced transition intensity. This work demonstrates a promising strategy by utilizing the alloy entropic effect to further improve the material stability and optoelectronic performance of halide perovskites.

Correction: MDM2 E3 ligase activity is essential for p53 regulation and cell cycle integrity.

[This corrects the article DOI: 10.1371/journal.pgen.1010171.].

Inorganic Crystal Structure Prototype Database Based on Unsupervised Learning of Local Atomic Environments.

Recognition of structure prototypes from tremendous known inorganic crystal structures has been an important subject beneficial for materials science research and new materials design. The existing databases of inorganic crystal structure prototypes were mostly constructed by classifying materials in terms of the crystallographic space group information. Herein, we employed a distinct strategy to construct the inorganic crystal structure prototype database, relying on the classification of materials in terms of local atomic environments (LAEs) accompanied by unsupervised machine learning method. Specifically, we adopted a hierarchical clustering approach onto all experimentally known inorganic crystal structure data to identify structure prototypes. The criterion for hierarchical clustering is the LAE represented by the state-of-the-art structure fingerprints of the improved bond-orientational order parameters and the smooth overlap of atomic positions. This allows us to build up a LAE-based Inorganic Crystal Structure Prototype Database (LAE-ICSPD) containing 15,613 structure prototypes with defined stoichiometries. In addition, we have developed a Structure Prototype Generator Infrastructure (SPGI) package, which is a useful toolkit for structure prototype generation. Our developed SPGI toolkit and LAE-ICSPD are beneficial for investigating inorganic materials in a global way as well as accelerating the materials discovery process in the data-driven mode.

MDM2 E3 ligase activity is essential for p53 regulation and cell cycle integrity.

MDM2 and MDM4 are key regulators of p53 and function as oncogenes when aberrantly expressed. MDM2 and MDM4 partner to suppress p53 transcriptional transactivation and polyubiquitinate p53 for degradation. The importance of MDM2 E3-ligase-mediated p53 regulation remains controversial. To resolve this, we generated mice with an Mdm2 L466A mutation that specifically compromises E2 interaction, abolishing MDM2 E3 ligase activity while preserving its ability to bind MDM4 and suppress p53 transactivation. Mdm2L466A/L466A mice exhibit p53-dependent embryonic lethality, demonstrating MDM2 E3 ligase activity is essential for p53 regulation in vivo. Unexpectedly, cells expressing Mdm2L466A manifest cell cycle G2-M transition defects and increased aneuploidy even in the absence of p53, suggesting MDM2 E3 ligase plays a p53-independent role in cell cycle regulation and genome integrity. Furthermore, cells bearing the E3-dead MDM2 mutant show aberrant cell cycle regulation in response to DNA damage. This study uncovers an uncharacterized role for MDM2's E3 ligase activity in cell cycle beyond its essential role in regulating p53's stability in vivo.

Small-Molecule MMRi62 Induces Ferroptosis and Inhibits Metastasis in Pancreatic Cancer via Degradation of Ferritin Heavy Chain and Mutant p53.

High frequency of KRAS and TP53 mutations is a unique genetic feature of pancreatic ductal adenocarcinoma (PDAC). TP53 mutation not only renders PDAC resistance to chemotherapies but also drives PDAC invasiveness. Therapies targeting activating mutant KRAS are not available and the outcomes of current PDAC treatment are extremely poor. Here, we report that MMRi62, initially identified as an MDM2-MDM4-targeting small molecule with p53-independent pro-apoptotic activity, shows anti-PDAC activity in vitro and in vivo. We show that MMRi62 inhibits proliferation, clonogenic, and spheroid growth of PDAC cells by induction of cell death. MMRi62-induced cell death in PDAC is characteristic of ferroptosis that is associated with increased autophagy, increased reactive oxygen species, and lysosomal degradation of NCOA4 and ferritin heavy chain (FTH1). In addition to induced degradation of FTH1, MMRi62 also induces proteasomal degradation of mutant p53. Interestingly, MMRi62-induced ferroptosis occurs in PDAC cell lines harboring either KRAS and TP53 double mutations or single TP53 mutation. In orthotopic xenograft PDAC mouse models, MMRi62 was capable of inhibiting tumor growth in mice associated with downregulation of NCOA4 and mutant p53 in vivo. Strikingly, MMRi62 completely abrogated metastasis of orthotopic tumors to distant organs, which is consistent with MMRi62's ability to inhibit cell migration and invasion in vitro. These findings identified MMRi62 as a novel ferroptosis inducer capable of suppressing PDAC growth and overcoming metastasis.

Effect of long-term intensive cholesterol control on the plaque progression in elderly based on CTA cohort study.

OBJECTIVES: To investigate the long-term effects of intensive LDL cholesterol-lowering treatments on lumen stenosis severity, plaque calcification, spotty calcifications, percent calcified plaque volume (PCPV), and Agatston coronary artery calcium score (CACS) based on coronary computed tomography angiography (CCTA) in elderly patients. METHODS: A total of 240 patients over 60 years old (comprising 754 lesions) who underwent serial CCTA were retrospectively enrolled in this 5-year cohort study. Patients were divided into three groups: an intensive lipid-lowering group, a lipid-lowering group, and a control group. The stenosis severity, plaque volume (PV), plaque composition, PCPV, and high-risk plaque (HRP) presence were quantitatively analyzed. The CACS was calculated at baseline and follow-up. RESULTS: All patients were male with an average age of 66.8 ± 5.8 years old. Over time, increases in the percentages of obstructive coronary lesions (p < 0.001) were observed. Compared with those at baseline, the percentage of obstructive lesions remained unchanged (p = 0.077), and the percentage of spotty calcifications significantly decreased (p < 0.05) at the follow-up CCTA scan in the intensive lipid-lowering group. Patients in the intensive lipid-lowering group demonstrated a higher progression in calcified PV, CACS, and PCPV (all p < 0.05), and a significantly greater attenuation in fibrous-fatty and lipid-rich PV (all p < 0.05) than patients in other groups. CONCLUSIONS: The PV and contents increased gradually with time in all groups. Intensive LDL-C lowering was associated with slower progression of stenosis severity and reduction of high-risk plaque features, with increased plaque calcification and higher progression in PCPV. Comprehensive serial plaque evaluations by CCTAs may contribute to further refinement of risk stratification and reasonable lipid-lowering treatment in elderly patients. KEY POINTS: • Intensive LDL-C lowering increased coronary calcification and percent calcified plaque volume progression. • Comprehensive serial plaque evaluations by serial CCTAs may help to refine risk stratification.

Risk predicting for acute coronary syndrome based on machine learning model with kinetic plaque features from serial coronary computed tomography angiography.

AIMS: More patients with suspected coronary artery disease underwent coronary computed tomography angiography (CCTA) as gatekeeper. However, the prospective relation of plaque features to acute coronary syndrome (ACS) events has not been previously explored. METHODS AND RESULTS: One hundred and one out of 452 patients with documented ACS event and received more than once CCTA during the past 12 years were recruited. Other 101 patients without ACS event were matched as case control. Baseline, follow-up, and changes of anatomical, compositional, and haemodynamic parameters [e.g. luminal stenosis, plaque volume, necrotic core, calcification, and CCTA-derived fractional flow reserve (CT-FFR)] were analysed by independent CCTA measurement core laboratories. Baseline anatomical, compositional, and haemodynamic parameters of lesions showed no significant difference between the two cohorts (P > 0.05). While the culprit lesions exhibited significant increase of luminal stenosis (10.18 ± 2.26% vs. 3.62 ± 1.41%, P = 0.018), remodelling index (0.15 ± 0.14 vs. 0.09 ± 0.01, P < 0.01), and necrotic core (4.79 ± 1.84% vs. 0.43 ± 1.09%, P = 0.019) while decrease of CT-FFR (-0.05 ± 0.005 vs. -0.01 ± 0.003, P < 0.01) and calcium ratio (-4.28 ± 2.48% vs. 4.48 ± 1.46%, P = 0.004) between follow-up CCTA and baseline scans in comparison to that of non-culprit lesion. The XGBoost model comprising the top five important plaque features revealed higher predictive ability (area under the curve 0.918, 95% confidence interval 0.861-0.968). CONCLUSIONS: Dynamic changes of plaque features are highly relative with subsequent ACS events. The machine learning model of integrating these lesion characteristics (e.g. CT-FFR, necrotic core, remodelling index, plaque volume, and calcium) can improve the ability for predicting risks of ACS events.

Metal Halide Semiconductors beyond Lead-Based Perovskites for Promising Optoelectronic Applications.

In recent decades, metal halide semiconductors represented by lead-based halide perovskites have shown broad potential in optoelectronic applications. This family of semiconductors differs from traditional tetrahedral semiconductors in crystalline structure, chemical bonding, electronic-structure features, optoelectronic properties, as well as material fabrication method. At present, difficulties arising from both intrinsic material properties (including Pb toxicity and long-term stability) and technological aspects hinder their large-scale commercialization. In this Perspective, we focus on up-and-coming lead-free metal halide semiconductors toward high-performance optoelectronic applications. We start by outlining the advantages of metal halide semiconductors and their physical and chemical underpinnings. We then review composition and structure, electronic structure, optoelectronic properties, and device applications according to classification into three material categories, i.e., three-dimensional halide perovskites, low-dimensional perovskites and perovskite-like materials, and materials beyond perovskites. We conclude with an outlook on the challenges and opportunities of metal halide semiconductors and the future development of the field.