DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion-cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the omega B97XD/6-31G/MM level to elucidate these mechanisms. Results suggest that the catalytic process follows a sequential, stepwise reaction in which the C5-C5 and C6-C6 bonds are cleaved in order, facilitated by a protonated E283. Activation free energies for these cleavages are calculated at 4.4 and 4.2 kcal center dot mol(-1), respectively. Protonation of E283 reduces electrostatic repulsion with CPD and forms dual hydrogen bonds with it and provides better solvation, stabilizing the CPD radical anion, particularly during intermediate state. This stabilization renders the initial splitting step exergonic, slows reverse reactions of the C5-C5 bond cleavage and electron transfer, and ensures a high quantum yield. Furthermore, the protonation state of E283 significantly affects the type of bond cleavage. Other residues in the active site were also investigated for their roles in the mechanism.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care. Drawing on 51,269 participants across 9 independent, geographically diverse datasets, an AI model identifies the etiologies contributing to dementia in individuals, harnessing a broad array of data, including demographics, medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and MRI to identify likely cases, yet effective practices remain variably applied and lacking in sensitivity and specificity. Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Our framework linked a fully convolutional network, which constructs high resolution maps of disease probability from local brain structure to a multilayer perceptron and generates precise, intuitive visualization of individual Alzheimer's disease risk en route to accurate diagnosis. The model was trained using clinically diagnosed Alzheimer's disease and cognitively normal subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 417) and validated on three independent cohorts: the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) (n = 382), the Framingham Heart Study (n = 102), and the National Alzheimer's Coordinating Center (NACC) (n = 582). Performance of the model that used the multimodal inputs was consistent across datasets, with mean area under curve values of 0.996, 0.974, 0.876 and 0.954 for the ADNI study, AIBL, Framingham Heart Study and NACC datasets, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n = 11), and high-risk cerebral regions predicted by the model closely tracked post-mortem histopathological findings. This framework provides a clinically adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease.

Tunable supramolecular nanoarchitectures have received enormous attention because of their potential in materials fabrication. Herein, a variety of morphologically intriguing nanoarchitectures have been constructed from diphenanthro-24-crown-8 ether (DPC) and metal ions. SEM and TEM showed that the self-assembled nanofibers undergo a CsI -induced transformation into regular nanoribbons, and further into nanospheres and nanoparticles by the complexation of NiII and AgI ions because of the strong ion-dipole interaction. Moreover, the X-ray crystal structure determination and powder X-diffraction data further confirmed that these morphological transformations resulted from the different complexation between DPC and metal ions. This result provides a new strategy for the subtle manipulation of supramolecular assemblies.

Combined homocysteinemia with methylmalonic aciduria (MMA/HCY) are genetic disorders of intracellular cobalamin (cbl) transport and processing that cause downstream deficiencies in methylcobalamin and adenosylcobalamin. Untreated disease is characterized biochemically by methylmalonic aciduria and hyperhomocysteinemia, while the clinical features are variable. When spastic paraplegia (SP) dominates, it is difficult to differentiate from hereditary spastic paraplegia (HSP). Clinical, biochemical and imaging features were reviewed in eight patients with MMA/HCY that mimicked HSP. Seven males and one female were enrolled. The median onset age was 13 years old (range 7–26 years old). The median time delay of diagnosis was 20.5 months (range 2–60 months). Spastic gait was the first symptom in four patients, while the other four patients presented with chronic emotional abnormalities or cognitive impairment. The main clinical manifestation was SP, and other neurological symptoms included cognitive impairment (5/8), spastic dysuria (3/8), personality change and depression (3/8), ataxia (2/8), seizures (2/8), limb numbness (2/8), and developmental delay (2/8). When patients were diagnosed, the mean serum homocysteine level, the methylmalonic acid level in urine, the serum propionylcarnitine (C3) level and the ratios of C3-to-acetylcarnitine (C2) and free carnitine (C0) were all dramatically elevated. Cranial MRIs showed nothing remarkable except mild brain atrophy. All spinal MRIs were normal except for case 8. Definite compound heterozygous mutations in MMACHC were detected in five cases. Follow-up indicated partial improvement in all the patients after intramuscular cbl, oral betaine and folate, supporting the diagnosis of MMA/HCY. Our data highlight the need for extensive investigation of intracellular cbl transport and processing, when spastic paraparesis is a prominent component of the clinical picture. Testing for urine methylmalonic acid and serum homocysteine levels is a simple but critical approach in suspected cases. Genetic testing, especially for MMACHC gene mutations, is needed. Raising awareness of this disorder could result in the timely initiation of targeted treatment, which may significantly improve patient outcomes.

针对消息传递接口(MPI)在高性能计算领域的应用场景,为了优化MPI现有数据集中管理模式,增强其对大数据的处理能力,借鉴并行与分布式系统思想,开发设计一套适用于大数据处理的基于MPI的数据存储组件(MPI-DSP).首先,创建接口函数,以对MPI系统影响最小的方式实现“计算向存储迁移”的设计目标,将文件分配与计算进行分离,使MPI突破大数据文件读取时的网络传输瓶颈.然后,分析阐述设计目标、运行机制、实现策略,通过描述接口函数MPI_Open在MPI环境下的应用,验证设计理念.通过Wordcount实验对比使用MPI-DSP组件与原MPI在数据文件处理方面的时间性能,初步验证了MPI“计算向存储迁移”模式的可行性,使其具备在高性能应用场景下的大数据处理能力.同时分析了MPI-DSP的适用环境和局限性,界定了其应用范围.

HlyB functions as an adenosine triphosphate (ATP)-binding cassette (ABC) transporter that enables bacteria to secrete toxins at the expense of ATP hydrolysis. Our previous work, based on potential energy profiles from combined quantum mechanical and molecular mechanical (QM/MM) calculations, has suggested that the highly conserved H-loop His residue H662 in the nucleotide binding domain (NBD) of E. coli HlyB may catalyze the hydrolysis of ATP through proton relay. To further test this hypothesis when entropic contributions are taken into account, we obtained QM/MM minimum free energy paths (MFEPs) for the HlyB reaction, making use of the string method in collective variables. The free energy profiles along the MFEPs confirm the direct participation of H662 in catalysis. The MFEP simulations of HlyB also reveal an intimate coupling between the chemical steps and a local protein conformational change involving the signature-loop residue S607, which may serve a catalytic role similar to an Arg-finger motif in many ATPases and GTPases in stabilizing the phosphoryl-transfer transition state.

A surface-enhanced Raman scattering (SERS) method has been developed to determine the concentration of trichloroethylene (TCE) in environmental water. Au-core/Ag-shell nanoparticles containing 4-mercaptophenylboronic acid (4-MPBA) between the core and shell are used as the SERS substrate. 4-MPBA serves as an internal reference with a Raman shift at 534 cm−1. TCE reacts with 4-mercaptopyridine (4-MPy) in a so-called Fujiwara reaction. With the presence of TCE in water, the consumption of 4-MPy results in a change in the intensity of its Raman signal at 1220 cm−1. The ratio of the Raman shift at 1220 cm−1 and 534 cm−1 decreases linearly in the 0.2 to 1.0 μM TCE concentration range, and the detection limit of TCE is as low as 8 ppb (60 nM). The method has been successfully applied to the determination of TCE in spiked lake water.

We report the development of a type of novel hybrid photosensitizers for photodynamic inactivation of broad-spectrum bacteria.

We report a thorough investigation of triplet–triplet annihilation upconversion (TTA-UC) in the silicone core/silica shell hollow nanoparticles (SSNPs). The results demonstrate that Platinum(II) octaethylporphyrin (PtOEP) and 9, 10-diphenylanthracene (DPA) were successfully captured in the hollow particles. It was also observed that TTA upconversion intensity from SSNPs increases with the concentration of DPA increasing. The mobility of chromophores was improved by the liquid core of the SSNPs, leading to the increasing of TTA-UC intensity. These results shed light onto the strategies to construct TTA-UC systems in solid substrates.

Surface-enhanced Raman scattering (SERS) has been widely studied and applied for over three decades. However, reliable SERS detection of molecules with low polarizability is still suffering from poor sensitivity and reproducibility. In this paper, we have reported a new strategy for performing quantitative SERS detection of Raman insensitive Glutathione (GSH), based on GSH-induced replacement of a highly Raman sensitive four-mercaptopyridine (MP) adsorbed on the surface of four-aminothiophenol (ATP) embedded Au-core/Ag-shell particles. This replacement led to a strong decrease of the MP SERS signal, which was used to determine the concentration of GSH. The adoption of GSH-induced Raman probe replacement leads to high sensitivity, while the use of internal reference method provides an improved accuracy of the GSH quantification.

利用过氧钼酸前驱物,通过水热法方法成功制备了具有新颖结构的亚稳六方相Ag1.028H1.852Mo5.52O18纳米棒状,对该纳米材料的微观形貌结构、光吸收性质和光致变色特性等进行了表征,研究了不同光照条件下该材料光致变色性能.FESEM和TEM的测试结果表明,Ag1.028H1.852Mo5.52O18纳米棒呈现出类似于火炬状的半中空结构,根据纳米棒形貌的时间演化情况,讨论了该火炬状结构的可能生长机理.此外,Ag1.028H1.852Mo5.52O18纳米棒展现出独特的多重颜色光致变色现象,在紫外光照射下依次发生由白色到蓝色、棕黄色、墨绿色的颜色变化,在通氧的黑暗环境下又恢复为原来的状态,具有良好的可重复光致变色特性.

We report a quantitative SERS measurement scheme based on the magnetic microsphere-Ag nanoparticles to detect target DNA. The quantitative SERS measurements can quantify the target DNA concentration down to 10 nM.

Analytical applications of SERS are often more associated with qualitative than quantitative analysis, because of the difficulty in obtaining quantitative SERS results. In this paper we introduce a new strategy to quantitatively measure the SERS signals of analytes based on Au-core/Ag-shell nanoparticles with embedded 4-aminothiophenol as the internal reference. Successful detections of two analytes, Toluidine Blue O in aqueous solution (detection limit of 0.1 μM) and melamine in milk (detection limit of ~5 μM), are demonstrated. The improvement in the linear fitting illustrates that the use of internal reference significantly improves the accuracy of the quantitative SERS measurements. The successful detection of melamine in milk illustrates the versatility of this detection scheme for a wide variety of analytes.

We demonstrate a methodology to prepare Au-core-Ag-shell nanoparticles displaying both SERS and surface-enhanced fluorescence (SEF) activities simultaneously by embedding dye molecules between the core and the shell. Polyelectrolytes are used to adjust the spacing and the dye position between the core and the shell. Layer-by-layer polyelectrolyte deposition can serve as an effective and flexible way to introduce various types of dye molecules into the nanostructures. Results from the spectral measurements shed light on the intricacy between SERS and SEF.

We report a method for quantitative SERS measurements using Ag–Fe3O4 nanocomposites with an internal reference for detecting different analytes.

Adenosine triphosphate (ATP)-binding cassette (ABC) transporters form a family of molecular motor proteins that couple ATP hydrolysis to substrate translocation across cell membranes. Each nucleotide binding domain of ABC-transporters contains a highly conserved H-loop histidine residue, whose precise mechanistic role in motor functions has remained elusive. By using combined quantum mechanical and molecular mechanical (QM/MM) calculations, we showed that the conserved H-loop residue H662 in E. coli HlyB, a bacterial ABC-transporter, can act first as a general acid and then as a general base to facilitate proton transfer in ATP hydrolysis. Without the assistance of H662, direct proton transfer from the lytic water to ATP results in a substantially higher barrier height. Our findings suggest that the essential function of the H-loop residue H662 is to provide a "chemical linchpin" that shuttles protons between reactants through a relay mechanism, thereby catalyzing ATP hydrolysis in HlyB.