Photodissociation dynamics of SO2 via the G̃1B1 state: The O(1D2) and O(1S0) product channels

Produced by both nature and human activities, sulfur dioxide (SO2) is an important species in the earth's atmosphere. SO2 has also been found in the atmospheres of other planets and satellites in the solar system. The photoabsorption cross sections and photodissociation of SO2 have been studied for several decades. In this paper, we reported the experimental results for photodissociation dynamics of SO2 via the G̃1B1 state. By analyzing the images from the time-sliced velocity map ion imaging method, the vibrational state population distributions and anisotropy parameters were obtained for the O(1D2) + SO(X3Σ-, a1Δ, b1Σ+) and O(1S0) + SO(X3Σ-) channels, and the branching ratios for the channels O(1D2) + SO(X3Σ-), O(1D2) + SO(a1Δ), and O(1D2) + SO(b1Σ+) were determined to be ∼0.3, ∼0.6, and ∼0.1, respectively. The SO products were dominant in electronically and rovibrationally excited states, which may have yet unrecognized roles in the upper planetary atmosphere.

Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in Alzheimer's disease

Current diagnostic systems for Alzheimer's disease (AD) rely upon clinical signs and symptoms, despite the fact that the multiplicity of clinical symptoms renders various neuropsychological assessments inadequate to reflect the underlying pathophysiological mechanisms. Since putative neuroimaging biomarkers play a crucial role in understanding the etiology of AD, we sought to stratify the diverse relationships between AD biomarkers and cognitive decline in the aging population and uncover risk factors contributing to the diversities in AD. To do so, we capitalized on a large amount of neuroimaging data from the ADNI study to examine the inflection points along the dynamic relationship between cognitive decline trajectories and whole-brain neuroimaging biomarkers, using a state-of-the-art statistical model of change point detection. Our findings indicated that the temporal relationship between AD biomarkers and cognitive decline may differ depending on the synergistic effect of genetic risk and biological sex. Specifically, tauopathy-PET biomarkers exhibit a more dynamic and age-dependent association with Mini-Mental State Examination scores (p<0.05), with inflection points at 72, 78, and 83 years old, compared with amyloid-PET and neurodegeneration (cortical thickness from MRI) biomarkers. In the landscape of health disparities in AD, our analysis indicated that biological sex moderates the rate of cognitive decline associated with APOE4 genotype. Meanwhile, we found that higher education levels may moderate the effect of APOE4, acting as a marker of cognitive reserve.

Spectroscopic and Theoretical Identifications of Two Structural Motifs of (H2O)10 Cluster

Precise characterization of archetypal systems of aqueous hydrogen-bonding networks is essential for developing accurate potential functions and universal models of water. The structures of water clusters (H2O)n (n = 2-9) have been verified recently through size-specific infrared spectroscopy with a vacuum ultraviolet free electron laser (VUV-FEL) and quantum chemical studies. For (H2O)10, the pentagonal prism and butterfly motifs were proposed to be important building blocks and were observed in previous experiments. Here we report the size-specific infrared spectra of (H2O)10 via a joint experimental and theoretical study. Well-resolved spectra provide a unique signature for the coexistence of pentagonal prism and butterfly motifs. These (H2O)10 motifs develop from the dominant structures of (H2O)n (n = 8, 9) clusters. This work provides an intriguing prelude to the diverse structure of liquid water and opens avenues for size-dependent measurement of larger systems to understand the stepwise formation mechanism of hydrogen-bonding networks.

Insights into ultrafast decay dynamics of electronically excited pyridine-N-oxide

The ultrafast decay dynamics of pyridine-N-oxide upon excitation in the near-ultraviolet range of 340.2-217.6 nm is investigated using the femtosecond time-resolved photoelectron imaging technique. The time-resolved photoelectron spectra and photoelectron angular distributions at all pump wavelengths are carefully analyzed and the following view is derived: at the longest pump wavelengths (340.2 and 325.6 nm), pyridine-N-oxide is excited to the S1(1ππ*) state with different vibrational levels. The depopulation rate of the S1 state shows a marked dependence on vibrational energy and mode, and the lifetime is in the range of 1.4-160 ps. At 289.8 and 280.5 nm, both the second 1ππ* state and the S1 state are initially prepared. The former has an extremely short lifetime of ∼60 fs, which indicates that the ultrafast deactivation pathway such as a rapid internal conversion to one close-lying state is its dominant decay channel, while the latter is at high levels of vibrational excitation and decays within the range of 380-520 fs. At the shortest pump wavelengths (227.3 and 217.6 nm), another excited state of Rydberg character is mostly excited. We assign this state to the 3s Rydberg state which has a lifetime of 0.55-2.2 ps. This study provides a comprehensive picture of the ultrafast excited-state decay dynamics of the photoexcited pyridine-N-oxide molecule.

[Analysis of ultrasound images features and diagnostic model establishment of alveolar soft part sarcoma and intramuscular capillary-type hemangiomas]

Objective: The ultrasonography features of alveolar soft part sarcoma (ASPS) and intramuscular capillary-type hemangiomas (ICTH) were analyzed, and the diagnostic model of ASPS was established. Methods: A cross-sectional study was carried out. The clinical data of 52 patients [28 males and 24 females, aged (20.7±15.1) years] with pathologically confirmed ASPS and ICTH admitted to People's Hospital of Henan Province from January 2005 to February 2023 were included in the study. According to pathological types, the patients were divided into ASPS group and ICTH group. Clinical data of patients were retrospectively collected, and meaningful indicators in the univariate analysis were included in the regression analysis for screening. After comprehensive consideration of clinical significance and statistical significance, eligible indicators were selected for inclusion in the regression analysis. Binary logistic regression analysis was used to screen the factors that distinguished the pathological types of ASPS and ICTH, and the diagnostic model was established. The area under receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic effectiveness of the diagnostic model in distinguishing ASPS from ICTH. Results: There were 20 patients in ASPS group, 10 males and 10 females, aged (26.9±13.5) years, and 32 patients in ICTH group, 18 males and 14 females, aged (16.8±15.0) years. The age difference between the ASPS group and the ICTH group was statistically significant (P<0.05), and there were statistically significant differences in the ultrasound imaging features of "clear boundary" "peripheral lobe" "thin blood vessels inside the lesion are straight and out of shape" "intra-lesion liquification" "peripheral thick blood vessels" and "peripheral muscle fiber disruption" between the two groups (all P<0.001).Variables with clinical and statistical significance were selected as independent variables. Binary logistic regression analysis showed that peripheral muscle fiber interruption (OR=97.358, 95%CI:6.833-1 387.249) and internal thin blood vessels were flat and out of shape (OR=0.052, 95%CI:0.003-0.921) was the correlation factor to distinguish the pathological types of ASPS and ICTH. Two ultrasonic image features of "peripheral muscle fiber interruption" and "internal thin blood vessels are straight and out of shape" were used to establish the diagnostic model. The sensitivity of "peripheral muscle fiber interruption" diagnostic model was 81.3%, and the specificity was 95.0%. The AUC was 0.811(95%CI: 0.761-0.954). The sensitivity, specificity and AUC of the diagnosis model of "internal thin vessels with flat misshape" were 90.0%, 96.9% and 0.934(95%CI: 0.830-0.984). The sensitivity, specificity and AUC of the combined diagnosis model of "peripheral muscle fiber interruption" and "internal thin blood vessel straight out of shape" were 96.9%, 90.0% and 0.974(95%CI:0.877-0.999). Conclusion: Ultrasonography can be used to distinguish ASPS from ICTH, and the combined diagnostic model based on the two ultrasonic imaging features of "peripheral muscle fiber interruption" and "internal thin blood vessel straight out of shape" can further improve the diagnostic efficiency.

Roaming in highly excited states: The central atom elimination of triatomic molecule decomposition

Chemical reactions are generally assumed to proceed from reactants to products along the minimum energy path (MEP). However, straying from the MEP-roaming-has been recognized as an unconventional reaction mechanism and found to occur in both the ground and first excited states. Its existence in highly excited states is however not yet established. We report a dissociation channel to produce electronically excited fragments, S(1D)+O2(a1Δg), from SO2 photodissociation in highly excited states. The results revealed two dissociation pathways: One proceeds through the MEP to produce vibrationally colder O2(a1Δg) and the other yields vibrationally hotter O2(a1Δg) by means of a roaming pathway involving an intramolecular O abstraction during reorientation motion. Such roaming dynamics may well be the rule rather than the exception for molecular photodissociation through highly excited states.

Time-Resolved Dynamics of Metal Halide Perovskite under High Pressure: Recent Progress and Challenges

Metal halide perovskites have garnered significant attention in the scientific community for their promising applications in optoelectronic devices. The application of pressure engineering, a viable technique, has played a crucial role in substantially improving the optoelectronic characteristics of perovskites. Despite notable progress in understanding ground-state structural changes under high pressure, a comprehensive exploration of excited-state dynamics influencing luminescence remains incomplete. This Perspective delves into recent advances in time-resolved dynamics studies of photoexcited metal halide perovskites under high pressure. With a focus on the intricate interplay between structural alterations and electronic properties, we investigate electron-phonon interactions, carrier transport mechanisms, and the influential roles of self-trapped excitons (STEs) and coherent phonons in luminescence. However, significant challenges persist, notably the need for more advanced measurement techniques and a deeper understanding of the phenomena induced by high pressure in perovskites.

Pathology steered stratification network for subtype identification in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by three neurobiological factors beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for AD at a late stage, urging for early detection and prevention. However, existing statistical inference approaches in neuroimaging studies of AD subtype identification do not take into account the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles.

PURPOSE

Integrating systems biology modeling with machine learning, the study aims to assist clinical AD prognosis by providing a subpopulation classification in accordance with essential biological principles, neurological patterns, and cognitive symptoms.

METHODS

We propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along the brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term evolution trajectories that capture individual characteristic progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations.

RESULTS

Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome.

CONCLUSIONS

The proposed PSSN (i) reduces neuroimage data to low-dimensional feature vectors, (ii) combines AT[N]-Net based on real pathological pathways, (iii) predicts long-term biomarker trajectories, and (iv) stratifies subjects into fine-grained subtypes with distinct neurological underpinnings. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases.

Quantitative CT features on admission combined with laboratory biomarkers for predicting severe acute pancreatitis

AIM

To assess the association of quantitative computed tomography (CT) features on admission with acute pancreatitis (AP) severity, and to explore the performance of combined CT and laboratory markers for predicting severe AP (SAP).

MATERIALS AND METHODS

Data from 208 AP patients were reviewed retrospectively. Pancreas volume, the area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were calculated based on CT images on admission. Laboratory biomarkers within 24 h of admission were collected. Interobserver agreement for CT measurements was measured by calculating interclass correlation coefficient (ICC). The associations of quantitative CT features with AP severity were evaluated. Predictive models for SAP were constructed based on CT and laboratory markers. Performances of single marker and the models were evaluated using receiver operating characteristic (ROC) curve and area under the ROC curve (AUC).

RESULTS

Pancreas volume, area of extrapancreatic inflammation, extrapancreatic fluid collection volume, and number were significantly different between severe and non-severe AP groups. In predicting SAP, the AUCs of quantitative CT indicators ranged from 0.72 to 0.79; the AUCs of laboratory biomarkers were between 0.53 and 0.66. The combined model of area of extrapancreatic inflammation, serum calcium, and haematocrit yielded an AUC of 0.84, significantly higher than that of the laboratory model, single CT, or laboratory marker. Interobserver agreements for quantitative CT indicators were excellent, with ICC ranging from 0.91 to 0.98.

CONCLUSION

Quantitative CT features on admission were significantly associated with AP severity; the combination of extrapancreatic inflammation area, serum calcium, and haematocrit could be taken as a new method for predicting SAP.

Effects of NO2 and SO2 on the secondary organic aerosol formation from β-pinene photooxidation

Elucidating the effects of anthropogenic pollutants on the photooxidation of biogenic volatile organic compounds is crucial to understanding the fundamental mechanisms of secondary organic aerosol (SOA) formation. Here, the impacts of NO2 and SO2 on SOA formation from the photooxidation of a representative monoterpene, β-pinene, were investigated by a number of laboratory studies. The results indicated NO2 enhanced the SOA mass concentrations and particle number concentrations under both low and high β-pinene conditions. This could be rationalized that the increased O3 concentrations upon the NOx photolysis was helpful for the generation of more amounts of O3-oxidized products, which accelerated the SOA nucleation and growth. Combing with NO2, the promotion of the SOA yield by SO2 was mainly reflected in the increase of mass concentration, which might be due to the elimination of the newly formed particles by the initially formed particles. The observed low oxidation degree of SOA might be attributed to the fast growth of SOA, resulting in the uptake of less oxygenated gas-phase species onto the particle phase. The present findings have important implications for SOA formation affected by anthropogenic-biogenic interactions in the ambient atmosphere.

The interaction effects of age, APOE and common environmental risk factors on human brain structure

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

Diamond-Like Carbon: A Surface for Extreme, High-Wear Environments

In this study, we present an in-depth characterization of a diamond-like carbon (DLC) film, using a range of techniques to understand the structure and chemistry of the film both in the interior and particularly at the DLC/air surface and DLC/liquid interface. The DLC film is found to be a combination of sp2 and sp3 carbon, with significant oxygen present at the surface. The oxygen seems to be present as OH groups, making the DLC somewhat hydrophilic. Quartz-Crystal Microbalance (QCM) isotherms and complementary neutron reflectivity data indicate significant adsorption of a model additive, bis(2-ethylhexyl) sulfosuccinate sodium salt (AOT) surfactant, onto the DLC from water solutions and indicate the adsorbed film is a bilayer. This initial study of the structure and composition of a model surfactant is intended to give a clearer insight into how DLC and additives function as antiwear systems.

Beyond Vision: A View from Eye to Alzheimer's Disease and Dementia

With the aging of the global population, the health care burden of Alzheimer's disease (AD) and dementia is considered to increase dramatically in the coming decades. Given the insufficiency of effective interventions for AD and dementia, clinical research on identifying potentially modifiable risk factors and early diagnostic biomarkers becomes a public health priority. Currently, extracerebral manifestations with a large proportion of ocular involvement are usually recognized to precede the symptoms of AD and dementia. Growing epidemiologic evidence also suggests that eye disorders, such as cataracts, age-related macular degeneration, glaucoma, diabetic retinopathy, and so on, are closely associated with and even have a higher incidence of AD and dementia. The eye, as an extension of the central nervous system, therefore has the potential to provide a feasible approach to detecting structural and functional abnormalities of the brain. Numerous new imaging modalities are developed and give novel insights into the detection of several neurodegenerative, vascular, neuropathological, and other ocular abnormalities of AD and dementia in scientific research and clinical application. This review provides an overview of the epidemiologic associations between eye disorders and AD or dementia and summarizes the recent advances in ocular examinations and techniques employed for the detection of AD and dementia. With more brain-and-eye interconnections being identified, the eye is becoming a noninvasive and easily accessible window for the early diagnosis and prevention of AD and dementia.

Factors influencing the detection rate of fumarate peak in 1H MR spectroscopy of fumarate hydratase-deficient renal cell carcinoma at 3 T MRI

AIM

To identify factors that may be associated with fumarate detection rate in 1H-magnetic resonance spectroscopy (MRS) in fumarate hydratase-deficient renal cell carcinoma (FH-RCC).

MATERIALS AND MEHODS

Between February 2018 and March 2022, 16 FH-RCC patients with 30 lesions underwent 1H-MRS. Detection results were classified as having a detected fumarate peak (n=12), undetected peak (n=10), or technical failure (n=8). Factors including tumour size, tumour location, treatment history, and metastasis status were collected and analysed. A Bayesian logistic regression model was applied to evaluate the association between these factors and the detection result.

RESULTS

Bayesian analysis demonstrated significant associations between fumarate detection results and the following factors: long-axis diameter (odds ratio [OR] of 1.64; 95% confidence interval [CI] of 1.07-2.53), short-axis diameter (OR of 1.90; 95% CI of 1.19-3.06), voxel size (OR of 2.85; 95% CI of 1.70-4.75), treatment history (OR of 0.35; 95% CI of 0.21-0.58), non-metastatic state (OR of 2.45; 95% CI of 1.48-4.06), and lymph node metastasis (OR of 0.35; 95% CI of 0.21-0.58). Technical failure results were associated with factors such as treatment history (OR of 2.59; 95% CI of 1.37-4.66), non-metastatic state (OR of 0.36; 95% CI of 0.19-0.66), and lymph node metastasis (OR of 2.61; 95% CI of 1.39-4.74).

CONCLUSION

Tumour size, treatment history, and metastasis character were associated with the detection of abnormal fumarate accumulation. This finding will serve as a reference for interpreting 1H-MRS results and for selecting suitable scenarios to evaluate FH-RCC.

Developing Explainable Deep Model for Discovering Novel Control Mechanism of Neuro-Dynamics

Human brain is a complex system composed of many components that interact with each other. A well-designed computational model, usually in the format of partial differential equations (PDEs), is vital to understand the working mechanisms that can explain dynamic and self-organized behaviors. However, the model formulation and parameters are often tuned empirically based on the predefined domain-specific knowledge, which lags behind the emerging paradigm of discovering novel mechanisms from the unprecedented amount of spatiotemporal data. To address this limitation, we sought to link the power of deep neural networks and physics principles of complex systems, which allows us to design explainable deep models for uncovering the mechanistic role of how human brain (the most sophisticated complex system) maintains controllable functions while interacting with external stimulations. In the spirit of optimal control, we present a unified framework to design an explainable deep model that describes the dynamic behaviors of underlying neurobiological processes, allowing us to understand the latent control mechanism at a system level. We have uncovered the pathophysiological mechanism of Alzheimer's disease to the extent of controllability of disease progression, where the dissected system-level understanding enables higher prediction accuracy for disease progression and better explainability for disease etiology than conventional (black box) deep models.

Clonal hematopoiesis related TET2 loss-of-function impedes IL1β-mediated epigenetic reprogramming in hematopoietic stem and progenitor cells

Clonal hematopoiesis (CH) is defined as a single hematopoietic stem/progenitor cell (HSPC) gaining selective advantage over a broader range of HSPCs. When linked to somatic mutations in myeloid malignancy-associated genes, such as TET2-mediated clonal hematopoiesis of indeterminate potential or CHIP, it represents increased risk for hematological malignancies and cardiovascular disease. IL1β is elevated in patients with CHIP, however, its effect is not well understood. Here we show that IL1β promotes expansion of pro-inflammatory monocytes/macrophages, coinciding with a failure in the demethylation of lymphoid and erythroid lineage associated enhancers and transcription factor binding sites, in a mouse model of CHIP with hematopoietic-cell-specific deletion of Tet2. DNA-methylation is significantly lost in wild type HSPCs upon IL1β administration, which is resisted by Tet2-deficient HSPCs, and thus IL1β enhances the self-renewing ability of Tet2-deficient HSPCs by upregulating genes associated with self-renewal and by resisting demethylation of transcription factor binding sites related to terminal differentiation. Using aged mouse models and human progenitors, we demonstrate that targeting IL1 signaling could represent an early intervention strategy in preleukemic disorders. In summary, our results show that Tet2 is an important mediator of an IL1β-promoted epigenetic program to maintain the fine balance between self-renewal and lineage differentiation during hematopoiesis.

Excitation Energy-Dependent Decay Dynamics of the S1 State of N-Methyl-2-pyridone

The UV-induced decay dynamics of N-methyl-2-pyridone is investigated using a femtosecond time-resolved photoelectron spectroscopy method. Irradiation in the wavelength range of 339.3-258.9 nm prepares N-methyl-2-pyridone molecules with very different vibrational levels of the S1(11ππ*) state. For v' = 0 (origin) and a few low-energy vibrational levels slightly above the S1 state origin, the radiative decay channel is in operation for some specific vibrations. This is revealed by the excited-state lifetime of ≫1 ns. In addition, some other nearby S1 vibronic states have a much shorter lifetime in the range of several picoseconds to a few tens of picoseconds, indicating that the radiation-less decay to the ground state (S0) via internal conversion is the dominant channel for them. As the pump wavelength slightly decreases, the radiative decay is suddenly not important at all, and the deactivation rate of the S1 state becomes faster. At shorter pump wavelengths, the lifetime of highly excited vibrational states of the S1 state further decreases with the increase in the vibrational excess energy. This study provides quantitative information about the excitation energy-dependent decay dynamics of the S1 state of N-methyl-2-pyridone. Methyl substitution effects on the excited-state dynamics of 2-pyridone are also discussed.

Roxadustat protects rat renal tubular epithelial cells from hypoxia-induced injury through the TGF-β1/Smad3 signaling pathway

OBJECTIVE

Roxadustat is used to treat renal anemia. The renoprotective effect of roxadustat needs to be further confirmed, and the mechanism of action is unknown. This study aims to evaluate the effect and mechanism of roxadustat in hypoxia-related nephropathy with the renal tubular epithelial cell line NRK-52E.

MATERIALS AND METHODS

The cell Counting Kit-8 (CCK-8) assay was employed to assess cellular proliferation in the current investigation. Flow cytometry was used to conduct cell apoptosis analysis. The utilization of electron microscopy facilitated the identification of changes in cellular ultrastructure. Immunofluorescence was used to detect the expression trend of hypoxia-inducible factor-1α (HIF-1α). The connective tissue growth factor (CTGF), transforming growth factor-β1 (TGF-β1), Smad family member 3 (Smad3), p-Smad3, α-smooth muscle actin (α-SMA), collagen I, and HIF-1α were assessed by western blotting. Real-time fluorescent quantitative PCR (RT-qPCR) was used to measure TGF-β1 and Smad3 mRNA.

RESULTS

Significant growth inhibition and increased apoptosis were observed in NRK-52E cells cultured under hypoxic conditions (1% and 5% O2), which can be rescued by roxadustat. From a morphological perspective, it has been observed that roxadustat can counteract cellular damage features produced by hypoxia. These features include the contraction of the nuclear envelope and an increase in the formation of apoptotic bodies. Roxadustat increases HIF-1α expression acutely at 24 h, followed by a gradual reduction of HIF-1α expression to levels significantly below that of the hypoxia group by 72 h. Roxadustat can also inhibit hypoxia-induced increased expression of CTGF, TGF-β1, p-Smad3, α-SMA, collagen I, and HIF-1α. Combined treatment with roxadustat and siRNA against TGF-β1 synergistically reduced the expression of CTGF and HIF-1α, while the effect on TGF-β1 and p-Smad3 were comparable to that of the individual treatment alone. Comparably, the combined administration of roxadustat and siRNA targeting Smad3 had a synergistic impact on diminishing the expression of CTGF.

CONCLUSIONS

These findings indicate that roxadustat attenuates experimental renal fibrosis likely by inhibiting the TGF-β1/Smad3 pathways, while its effect on CTGF and HIF-1α may involve other signaling pathways.

Evidence of Surface-Mediated Carrier-Phonon Scattering in MXene

In a two-dimensional (2D) metallic nanostructure, when a sample's thickness is shorter than a carrier mean free path, the ultrathin thickness may influence carrier and energy transport, owing to surface scattering. However, to date, for metallic 2D transition-metal carbides (MXenes), experiments and calculations related to surface scattering have not been performed. The contribution of ultrathin structures to carrier surface scattering in MXene is yet to be explored. Herein, to reveal this effect, we design various models, including metal/MXene, dielectric/MXene, and bulk structure, and analyze their carrier dynamics via ultrafast spectroscopy. The results related to carrier dynamics indicate that the influence of the dielectric/MXene interface and the temperature is negligible. In contrast, the carrier dynamic lifetimes are prolonged owing to weakened surface scattering in metal/MXene, which is supported by ab initio calculations. These results suggest that the carrier-phonon scattering is dominated by surface scattering. These findings can help guide effective energy transport and enhance energy conversion and catalysis.

Manipulating Lone-Pair-Driven Luminescence in 0D Tin Halides by Pressure-Tuned Stereochemical Activity from Static to Dynamic

The excellent luminescence properties and structural dynamics driven by the stereoactivity of the lone pair in a variety of low-dimensional ns2 metal halides have attracted growing investigations for optoelectronic applications. However, the structural and photophysical aspects of the excited state associated with the lone pair expression are currently open questions. Herein, zero-dimensional Sn-based halides with static stereoactive 5 s2 lone pairs are selected as a model system to understand the correlations between the distinctive lone pair expression and the excited-state structural relaxation and charge carrier dynamics by continuous lattice manipulation. Lattice compression drives 5 s2 lone pair active switching and self-trapped exciton (STE) redistribution by suppressing excited-state structural deformation of the isolated SnBr4 2- units. Our results demonstrate that the static expression of the 5 s2 lone pair results in a red broadband triplet STE emission with a large Stokes shift, while its dynamic expression creates a sky-blue narrowband emission dominated by the radiative recombination of singlet STEs. Our findings and the photophysical mechanism proposed highlight the stereochemical effects of lone pair expression in controlling light emission properties and offer constructive guidelines for tuning the optoelectronic properties in diverse ns2 metal halides.

Uncovering Diverse Mechanistic Spreading Pathways in Disease Progression of Alzheimer's Disease

Background

The AT[N] research framework focuses on three major biomarkers in Alzheimer's disease (AD): amyloid-β deposition (A), pathologic tau (T), and neurodegeneration [N].

Objective

We hypothesize that the diverse mechanisms such as A⟶T and A⟶[N] pathways from one brain region to others, may underlie the wide variation in clinical symptoms. We aim to uncover the causal-like effect of regional AT[N] biomarkers on cognitive decline as well as the interaction with non-modifiable risk factors such as age and APOE4.

Methods

We apply multi-variate statistical inference to uncover all possible mechanistic spreading pathways through which the aggregation of an upstream biomarker (e.g., increased amyloid level) in a particular brain region indirectly impacts cognitive decline, via the cascade build-up of a downstream biomarker (e.g., reduced metabolism level) in another brain region. Furthermore, we investigate the survival time for each identified region-to-region pathological pathway toward the AD onset.

Results

We have identified a collection of critical brain regions on which the amyloid burdens exert an indirect effect on the decline in memory and executive function (EF) domain, being mediated by the reduction of metabolism level at other brain regions. APOE4 status has been found not only involved in many A⟶N mechanistic pathways but also significantly contributes to the risk of developing AD.

Conclusion

Our major findings include 1) the region-to-region A⟶N⟶MEM and A⟶N⟶MEM pathways exhibit distinct spatial patterns; 2) APOE4 is significantly associated with both direct and indirect effects on the cognitive decline while sex difference has not been identified in the mediation analysis.

Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis

Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network much earlier before the onset of clinical symptoms, making its early diagnosis possible. Current brain network analyses treat high-dimensional network data as a regular matrix or vector, which destroys the essential network topology, thereby seriously affecting diagnosis accuracy. In this context, harmonic waves provide a solid theoretical background for exploring brain network topology. However, the harmonic waves are originally intended to discover neurological disease propagation patterns in the brain, which makes it difficult to accommodate brain disease diagnosis with high heterogeneity. To address this challenge, this article proposes a network manifold harmonic discriminant analysis (MHDA) method for accurately detecting AD. Each brain network is regarded as an instance drawn on a Stiefel manifold. Every instance is represented by a set of orthonormal eigenvectors (i.e., harmonic waves) derived from its Laplacian matrix, which fully respects the topological structure of the brain network. An MHDA method within the Stiefel space is proposed to identify the group-dependent common harmonic waves, which can be used as group-specific references for downstream analyses. Extensive experiments are conducted to demonstrate the effectiveness of the proposed method in stratifying cognitively normal (CN) controls, mild cognitive impairment (MCI), and AD.

Vacuum ultraviolet photodissociation of sulfur dioxide and its implications for oxygen production in the early Earth's atmosphere

The emergence of molecular oxygen (O2) in the Earth's primitive atmosphere is an issue of major interest. Although the biological processes leading to its accumulation in the Earth's atmosphere are well understood, its abiotic source is still not fully established. Here, we report a new direct dissociation channel yielding S(1D) + O2(a1Δg/X3Σg-) products from vacuum ultraviolet (VUV) photodissociation of SO2 in the wavelength range between 120 and 160 nm. Experimental results show O2 production to be an important channel from SO2 VUV photodissociation, with a branching ratio of 30 ± 5% at the H Lyman-α wavelength (121.6 nm). The relatively large amounts of SO2 emitted from volcanic eruptions in the Earth's late Archaean eon imply that VUV photodissociation of SO2 could have provided a crucial additional source term in the O2 budget in the Earth's primitive atmosphere. The results could also have implications for abiotic oxygen formation on other planets with atmospheres rich in volcanically outgassed SO2.

Exploring the Potential Applications of Lanthanide-Based Double Perovskite in Remote Pressure and Temperature Sensing

Remote optical sensing with nondestructive, fast, and accurate detection capabilities is a powerful noncontact method widely used in natural, industrial, and biological fields. In this work, Cs₂NaErCl₆ double perovskite was synthesized via a hydrothermal method. The pressure-dependent photoluminescence (PL) lifetime of Er³⁺ in the range of 0-20 GPa was investigated, demonstrating its potential for pressure monitoring. The high-pressure relative sensitivity (S_R) is ∼18.45% GPa^-1. Temperature measurements were conducted using the fluorescence intensity ratio (FIR) of the thermal couple energy level (TCEL) and the nonthermal couple energy level (NTCEL) of Er³⁺ across a temperature range of 100-660 K, with a maximum S_R of 5.36% K^-1. By combining MXene with Cs₂NaErCl₆ and recording the FIR of Cs₂NaErCl₆ under 1550 nm excitation, the photothermal conversion temperature of MXene can be accurately determined. These findings highlight the potential of Cs₂NaErCl₆ for remote pressure and temperature sensing, particularly in the biomedical field.

Effects of C-H stretching excitation on the dynamics of the O(1D) + CHD3 → OH/OD + CD3/CHD2 reaction

The vibrationally excited reaction O(1D) + CHD3(ν1 = 1) has been investigated by crossed-molecular-beam experiments with a time-sliced velocity map imaging technique. Detailed and quantitative information is extracted on the C-H stretching excitation effects on the reactivity and dynamics of the title reaction, with the help of preparation of C-H stretching excited CHD3 molecules by direct infrared excitation. Experimental results show that the vibrational stretching excitation of the C-H bond almost does not affect the relative contributions between different dynamical pathways for all product channels. For the OH + CD3 product channel, the vibrational energy of the C-H stretching excited CHD3 reagent is channeled exclusively into the vibrational energy of the OH products. The vibrational excitation of the CHD3 reactant changes the reactivities for the ground-state and umbrella-mode-excited CD3 channels very modestly, while it significantly suppresses the corresponding CHD2 channels. For the CHD2(ν1 = 1) channel, the stretching excited C-H bond of the CHD3 molecule acts almost as a pure spectator.

Learning pyramidal multi-scale harmonic wavelets for identifying the neuropathology propagation patterns of Alzheimer's disease

Previous studies have established that neurodegenerative disease such as Alzheimer's disease (AD) is a disconnection syndrome, where the neuropathological burdens often propagate across the brain network to interfere with the structural and functional connections. In this context, identifying the propagation patterns of neuropathological burdens sheds new light on understanding the pathophysiological mechanism of AD progression. However, little attention has been paid to propagation pattern identification by fully considering the intrinsic properties of brain-network organization, which plays an important role in improving the interpretability of the identified propagation pathways. To this end, we propose a novel harmonic wavelet analysis approach to construct a set of region-specific pyramidal multi-scale harmonic wavelets, it allows us to characterize the propagation patterns of neuropathological burdens from multiple hierarchical modules across the brain network. Specifically, we first extract underlying hub nodes through a series of network centrality measurements on the common brain network reference generated from a population of minimum spanning tree (MST) brain networks. Then, we propose a manifold learning method to identify the region-specific pyramidal multi-scale harmonic wavelets corresponding to hub nodes by seamlessly integrating the hierarchically modular property of the brain network. We estimate the statistical power of our proposed harmonic wavelet analysis approach on synthetic data and large-scale neuroimaging data from ADNI. Compared with the other harmonic analysis techniques, our proposed method not only effectively predicts the early stage of AD but also provides a new window to capture the underlying hub nodes and the propagation pathways of neuropathological burdens in AD.

Excitation wavelength dependent S1-state decay dynamics of 2-aminopyridine and 3-aminopyridine

The decay dynamics of 2-aminopyridine and 3-aminopyridine excited to the S₁ state is investigated using femtosecond time-resolved photoelectron imaging. The lifetime of the S₁ state for both molecules shows a rapid decrease with the increase of the vibrational energy. It is shown that, besides intersystem crossing to the lower-lying triplet state of T₁, the decay to the ground state (S₀) via internal conversion through a conical intersection plays an increasingly important role and becomes dominant for vibrational states well above the S₁ state origin. The comparison between 2-aminopyridine and 3-aminopyridine suggests that the intramolecular hydrogen bonding between a hydrogen atom of the NH₂ group and the heterocyclic nitrogen atom in 2-aminopyridine effectively hinders the ring deformation at lower vibrational states which is required for the wavepacket to reach the S₁/S₀ conical intersection, and therefore slows down the S₁ to S₀ internal conversion.

Sulfur Poisoning and Self-Recovery of Single-Site Rh1/Porous Organic Polymer Catalysts for Olefin Hydroformylation

Sulfur poisoning and regeneration are global deadly challenges for metal catalysts even at the ppm level. Fewer light was shed on the sulfur poisoning of single-metal-site catalysts and their regeneration. Herein, sulfur poisoning but self-recovery are first presented on an industrialized single-Rh-site catalyst (Rh1/POPs). A decreased turnover frequency of Rh1/POPs from 4317 h-1 to 318 h-1 was observed in a 1000 ppm H2S co-feed for ethylene hydroformylation, but it self-recovered to 4527 h-1 after withdrawal of H2S, while the rhodium nanoparticles demonstrated poor activity and self-recovery ability. H2S reduced the charge density of the single Rh atom and lowered its Gibbs free energy with the formation of inactive (SH)Rh(CO)(PPh3-frame)2, which could be regenerated to active HRh(CO)(PPh3-frame)2 after withdrawing H2S. The mechanism and the sulfur-related structure-activity relationship were highlighted. This work provides a forward understanding of the heterogeneous ethylene hydroformylation and the sulfur-poisoned regeneration in the catalysis science of single-atom catalysts.

Estimating Outlier-Immunized Common Harmonic Waves for Brain Network Analyses on the Stiefel Manifold

Since brain network organization is essentially governed by the harmonic waves derived from the Eigen-system of the underlying Laplacian matrix, discovering the harmonic-based alterations provides a new window to understand the pathogenic mechanism of Alzheimer's disease (AD) in a unified reference space. However, current reference (common harmonic waves) estimation studies over the individual harmonic waves are often sensitive to outliers, which are obtained by averaging the heterogenous individual brain networks. To address this challenge, we propose a novel manifold learning approach to identify a set of outlier-immunized common harmonic waves. The backbone of our framework is calculating the geometric median of all individual harmonic waves on the Stiefel manifold, instead of Fréchet mean, thus improving the robustness of learned common harmonic waves to the outliers. A manifold optimization scheme with theoretically guaranteed convergence is tailored to solve our method. The experimental results on synthetic data and real data demonstrate that the common harmonic waves learned by our approach are not only more robust to the outliers than the state-of-the-art methods, but also provide a putative imaging biomarker to predict the early stage of AD.

Towards texture accurate slice interpolation of medical images using PixelMiner

Quantitative image analysis models are used for medical imaging tasks such as registration, classification, object detection, and segmentation. For these models to be capable of making accurate predictions, they need valid and precise information. We propose PixelMiner, a convolution-based deep-learning model for interpolating computed tomography (CT) imaging slices. PixelMiner was designed to produce texture-accurate slice interpolations by trading off pixel accuracy for texture accuracy. PixelMiner was trained on a dataset of 7829 CT scans and validated using an external dataset. We demonstrated the model's effectiveness by using the structural similarity index (SSIM), peak signal to noise ratio (PSNR), and the root mean squared error (RMSE) of extracted texture features. Additionally, we developed and used a new metric, the mean squared mapped feature error (MSMFE). The performance of PixelMiner was compared to four other interpolation methods: (tri-)linear, (tri-)cubic, windowed sinc (WS), and nearest neighbor (NN). PixelMiner produced texture with a significantly lowest average texture error compared to all other methods with a normalized root mean squared error (NRMSE) of 0.11 (p < .01), and the significantly highest reproducibility with a concordance correlation coefficient (CCC) ≥ 0.85 (p < .01). PixelMiner was not only shown to better preserve features but was also validated using an ablation study by removing auto-regression from the model and was shown to improve segmentations on interpolated slices.

Revealing the Mechanism of Pressure-Induced Emission in Layered Silver-Bismuth Double Perovskites

Pressure-induced emission (PIE) associated with self-trapping excitons (STEs) in low-dimensional halide perovskites has attracted great attention for better materials-by-design. Here, using 2D layered double perovskite (C₆ H₅ CH₂ CH₂ NH₃ ⁺ )₄ AgBiBr₈ as a model system, we advance a fundamental physicochemical mechanism of the PIE from the perspective of carrier dynamics and excited-state behaviors of local lattice distortion. We observed a pressure-driven STE transformation from dark to bright states, corresponding a strong broadband Stokes-shifted emission. Further theoretical analysis demonstrated that the suppressed lattice distortion and enhanced electronic dimensionality in the excited-state play an important role in the formation of stabilized bright STEs, which could manipulate the self-trapping energy and lattice deformation energy to form an energy barrier between the potential energy curves of ground- and excited-state, and enhance the electron-hole orbital overlap, respectively.

Tailoring the high-brightness "warm" white light emission of two-dimensional perovskite crystals via a pressure-inhibited nonradiative transition

Efficient warm white light emission is an ideal characteristic of single-component materials for light-emitting applications. Although two-dimensional hybrid perovskites are promising candidates for light-emitting diodes, as they possess broadband self-trapped emission and outstanding stability, they rarely achieve a high photoluminescence quantum yield of warm white light emissions. Here, an unusual pressure-induced warm white emission enhancement phenomenon from 2.1 GPa to 9.9 GPa was observed in two-dimensional perovskite (2meptH2)PbCl4, accompanied by a large increase in the relative quantum yield of photoluminescence. The octahedral distortions, accompanied with the evolution of organic cations, triggered the structural collapse, which caused the sudden emission enhancement at 2.1 GPa. Afterwards, the further intra-octahedral collapse promotes the formation of self-trapped excitons and the substantial suppression of nonradiative transitions are responsible for the continuous pressure-induced photoluminescence enhancement. This study not only clearly illustrates the relationship between crystal structure and photoluminescence, but also provides an experimental basis for the synthesis of high-quality warm white light-emitting 2D metal halide perovskite materials.

The vibronic state dependent predissociation of H2S: determination of all fragmentation processes

Photochemistry plays a significant role in shaping the chemical reaction network in the solar nebula and interstellar clouds. However, even in a simple triatomic molecule photodissociation, determination of all fragmentation processes is yet to be achieved. In this work, we present a comprehensive study of the photochemistry of H₂S, derived from cutting-edge translational spectroscopy measurements of the H, S(¹D) and S(¹S) atom products formed by photolysis at wavelengths across the range 155-120 nm. The results provide detailed insights into the energy disposal in the SH(X), SH(A) and H₂ co-fragments, and the atomisation routes leading to two H atoms along with S(³P) and S(¹D) atoms. Theoretical calculations allow the dynamics of all fragmentation processes, especially the bimodal internal energy distributions in the diatomic products, to be rationalised in terms of non-adiabatic transitions between potential energy surfaces of both ¹A' and ¹A'' symmetry. The comprehensive picture of the wavelength-dependent (or vibronic state-dependent) photofragmentation behaviour of H₂S will serve as a text-book example illustrating the importance of non-Born-Oppenheimer effects in molecular photochemistry, and the findings should be incorporated in future astrochemical modelling.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms

PURPOSE

Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration.

METHODS

We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC).

RESULTS

A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity.

CONCLUSION

ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

Spectroscopic snapshot for neutral water nonamer (H2O)9: Adding a H2O onto a hydrogen bond-unbroken edge of (H2O)8

Structural characterization of neutral water clusters is crucial to understanding the structures and properties of water, but it has been proven to be a challenging experimental target due to the difficulty in size selection. Here, we report the size-specific infrared spectra of confinement-free neutral water nonamer (H₂O)₉ based on threshold photoionization, using a tunable vacuum ultraviolet free-electron laser. Distinct OH stretch vibrational fundamentals in the 3200-3350 cm^-1 region are observed, providing unique spectral signatures for the formation of an unprecedented (H₂O)₉ structure evolved by adding a ninth water molecule onto a hydrogen bond-unbroken edge of the (H₂O)₈ octamer with D_2d symmetry. This nonamer structure coexists with the five previously identified structures that can be viewed as derived by inserting a ninth water molecule into a hydrogen bond-broken edge of the D_2d/S₄ octamer. These findings provide key microscopic information for systematic understanding of the formation and growth mechanism of dynamical hydrogen-bonding networks that are responsible for the structure and properties of condensed-phase water.

Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer's Disease

BACKGROUND

Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-β (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.

OBJECTIVE

To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology.

METHODS

In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains.

RESULTS

Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development.

CONCLUSIONS

Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-β and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.

Anomalous Dynamics of Defect-Assisted Phonon Recycling in Few-Layer Mo0.5W0.5S2

Alloying has emerged as a new strategy to tune the function of 2D transition metal dichalcogenides (TMDCs). However, the lack of research on the electrical and structural properties of these alloys limits their practical applications. Here, femtosecond transient absorption spectroscopy with pump pulse tunability is performed to elucidate the ultrafast carrier dynamics in the few-layer Mo_0.5W_0.5S₂ prepared by the liquid phase exfoliation method. An anomalous rebleaching of the ground state is observed at high pump fluence by 3.1 eV excitation. We ascribe this rebleaching of the ground state to the mechanism that the carriers trapped in the defect are thermally excited back to the untrapped exciton state due to the phonon recycling, which hinders the dissipation of nonradiative energy, through comparative experiments and global analysis. Our findings demonstrate a novel energy transfer channel assisted by defect in few-layer TMDCs which is critical for their advanced applications.

Group-Wise Hub Identification by Learning Common Graph Embeddings on Grassmannian Manifold

Human brain is a complex yet economically organized system, where a small portion of critical hub regions support the majority of brain functions. The identification of common hub nodes in a population of networks is often simplified as a voting procedure on the set of identified hub nodes across individual brain networks, which ignores the intrinsic data geometry and partially lacks the reproducible findings in neuroscience. Hence, we propose a first-ever group-wise hub identification method to identify hub nodes that are common across a population of individual brain networks. Specifically, the backbone of our method is to learn common graph embedding that can represent the majority of local topological profiles. By requiring orthogonality among the graph embedding vectors, each graph embedding as a data element is residing on the Grassmannian manifold. We present a novel Grassmannian manifold optimization scheme that allows us to find the common graph embeddings, which not only identify the most reliable hub nodes in each network but also yield a population-based common hub node map. Results of the accuracy and replicability on both synthetic and real network data show that the proposed manifold learning approach outperforms all hub identification methods employed in this evaluation.

[Application of branch-first technique in total thoracic aorta replacement: short and medium term effect of 11 cases]

Objective: To examine the short and medium term effect of branch-first technique in total thoracic aorta replacement. Methods: The clinical data of eleven patients with ascending aortic aneurysms or type A aortic dissection+Crawford Ⅰ or Ⅱ total thoracoabdominal aortic aneurysm who were treated at Department of Cardiovascular Surgery in Henan Province Chest Hospital from January 2018 to July 2021 were retrospectively analyzed. There were 7 males and 4 females, aging (38±5) years (range: 28 to 45 years), 7 cases of whom were diagnosed with Marfan syndrome, 1 case was diagnosed with coarctation of aorta. Operations were performed under mild hypothermic and branch-first technique. Firstly, the middle and small incision in the chest was combined with the 6th intercostal incision in the left posterior lateral side. Secondly, four branches artificial blood vessels were anastomosed with the brachiocephalic artery to ensure the blood supply to the brain. After the circulation was blocked, intracardiac and aortic proximal operations were performed. Intercostal artery reconstruction and thoracic descending aorta replacement were completed after opening circulation. Results: The operative time of this group was (645.9±91.7) minutes (range: 505 to 840 minutes). One case had cerebral infarction and 1 case had chylothorax. The patients were followed up 4 to 47 months, 1 patient underwent thoracic and abdominal aorta+iliac artery resection and replacement due to the progression of abdominal aortic aneurysm 3 months after operation. Intercostal artery obstruction occurred in 2 cases, and the rest lived well. Conclusions: One-stage whole thoracic aorta replacement with branch-first technique has satisfactory results in the short and medium term, with no risk of residual aortic aneurysm rupture. It is an effective treatment for young and organs function well patients with complex aortic lesions.

Photodissociation of H2S: A New Pathway for the Production of Vibrationally Excited Molecular Hydrogen in the Interstellar Medium

Hydrogen sulfide (H₂S) is the most abundant S-bearing molecule in the solar nebula. Although its photochemistry has been studied for decades, the H₂ fragment channel is still not well-understood. Herein, we describe the photodissociation dynamics of H₂S + hv → S(¹S) + H₂(X¹Σ_g⁺) with the excitation wavelength of 122 nm ≤ λ ≤ 136 nm. The results reveal that the H₂(X) fragments formed are significantly vibrationally excited, with the quantum yields of ∼87% of H₂(X) fragments populated in vibrational levels v″ = 3, 4, 5, and 6. Theoretical analysis suggest that these H₂ products are formed on the H₂S 4¹A' state surface following a nonadiabatic transition via an avoided crossing from the 3¹A' to 4¹A' state. The estimated quantum yield of the S(¹S) + H₂ channel is ∼0.05, implying this channel should be incorporated into the appropriate interstellar chemistry models.

Learning Brain Dynamics of Evolving Manifold Functional MRI Data Using Geometric-Attention Neural Network

Functional connectivities (FC) of brain network manifest remarkable geometric patterns, which is the gateway to understanding brain dynamics. In this work, we present a novel geometric-attention neural network to characterize the time-evolving brain state change from the functional neuroimages by tracking the trajectory of functional dynamics on high-dimension Riemannian manifold of symmetric positive definite (SPD) matrices. Specifically, we put the spotlight on learning the common state-specific manifold signatures that represent the underlying cognition. In this context, the driving force of our neural network is tied up with the learning of the evolution functionals on the Riemannian manifold of SPD matrix that underlies the known evolving brain states. To do so, we train a convolution neural network (CNN) on the Riemannian manifold of SPD matrices to seek for the putative low-dimension feature representations, followed by an end-to-end recurrent neural network (RNN) to yield the time-varying mapping function of SPD matrices which fits the evolutionary trajectories of the underlying states. Furthermore, we devise a geometric attention mechanism in CNN, allowing us to discover the latent geometric patterns in SPD matrices that are associated with the underlying states. Notably, our work has the potential to understand how brain function emerges behavior by investigating the geometrical patterns from functional brain networks, which is essentially a correlation matrix of neuronal activity signals. Our proposed manifold-based neural network achieves promising results in predicting brain state changes on both simulated data and task functional neuroimaging data from Human Connectome Project, which implies great applicability in neuroscience studies.

Vibrational-state dependent decay dynamics of 2-pyridone excited to the S1 electronic state

The S₁(¹ππ*) state decay dynamics of 2-pyridone excited around the 000 band origin is investigated using femtosecond time-resolved photoelectron imaging technique. At a pump wavelength of 334.0 nm, the vibrational ground state and a few low energy vibrational states covered by the bandwidth of the pump laser pulses are excited. The lifetimes of the vibrational states show strong dependence on the vibrational energy and mode. A quantum beat between two lowest energy vibrational states is also observed. This study provides quantitative information about the vibrational-state dependent lifetime of the S₁ state of 2-pyridone.