High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs

Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of $10$ to $10^3$ depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.Comment: work presented in NYSDS 201

SMURF1 Attenuates Endoplasmic Reticulum Stress by Promoting the Degradation of KEAP1 to Activate NRF2 Antioxidant Pathway

Cancer cells consistently utilize the unfolded protein response (UPR) to encounter the abnormal endoplasmic reticulum (ER) stress induced by the accumulation of misfolded proteins. Extreme activation of the UPR could also provoke maladaptive cell death. Previous reports have shown that NRF2 antioxidant signaling is activated by UPR and serves as noncanonical pathway to defense and reduce excessive ROS levels during ER stress. However, the mechanisms of regulating NRF2 signaling upon ER stress in glioblastoma have not been fully elucidated. Here we identify that SMURF1 protects against ER stress and facilitates glioblastoma cell survival by rewiring KEAP1-NRF2 pathway. We show that ER stress induces SMURF1 degradation. Knockdown of SMURF1 upregulates IRE1 and PERK signaling in the UPR pathway and prevents ER-associated protein degradation (ERAD) activity, leading to cell apoptosis. Importantly, SMURF1 overexpression activates NRF2 signaling to reduce ROS levels and alleviate UPR-mediated cell death. Mechanistically, SMURF1 interacts with and ubiquitinates KEAP1 for its degradation (NRF2 negative regulator), resulting in NRF2 nuclear import. Moreover, SMURF1 loss reduces glioblastoma cell proliferation and growth in subcutaneously implanted nude mice xenografts. Taken together, SMURF1 rewires KEAP1-NRF2 pathway to confer resistance to ER stress inducers and protect glioblastoma cell survival. ER stress and SMURF1 modulation may provide promising therapeutic targets for the treatment of glioblastoma

Epigenome-wide association study on diffusing capacity of the lung

Background: Epigenetics may play an important role in the pathogenesis of lung diseases. However, little is known about the epigenetic factors that influence impaired gas exchange at the lung. Aim: To identify the epigenetic signatures of the diffusing capacity of the lung measured by carbon monoxide uptake (the diffusing capacity of the lung for carbon monoxide (DLCO)). Methods: An epigenome-wide association study (EWAS) was performed on diffusing capacity, measured by carbon monoxide uptake (DLCO) and per alveolar volume (VA) (as DLCO/VA), using the single-breath technique in 2674 individuals from two population-based cohort studies. These were the Rotterdam Study (RS, the "discovery panel") and the Framingham Heart Study (FHS, the "replication panel"). We assessed the clinical relevance of our findings by investigating the identified sites in whole blood and by lung tissue specific gene expression. Results: We identified and replicated two CpG sites (cg05575921 and cg05951221) that were significantly associated with DLCO/VA and one (cg05575921) suggestively associated with DLCO. Furthermore, we found a positive association between aryl hydrocarbon receptor repressor (AHRR) gene (cg05575921) hypomethylation and gene expression of exocyst complex component 3 (EXOC3) in whole blood. We confirmed that the expression of EXOC3 in lung tissue is positively associated with DLCO/VA and DLCO. Conclusions: We report on epigenome-wide associations with diffusing capacity in the general population. Our results suggest EXOC3 to be an excellent candidate, through which smoking-induced hypomethylation of AHRR might affect pulmonary gas exchange

Management of Tamm-Horsfall Protein for Reliable Urinary Analytics

Purpose Urinary extracellular vesicles (uEVs) are a novel source of biomarkers. However, urinary Tamm-Horsfall Protein (THP; uromodulin) interferes with all vesicle isolation attempts, precipitates with normal urinary proteins, thus, representing an unwanted "contaminant" in urinary assays. Thus, the aim is to develop a simple method to manage THP efficiently. Experimental design The uEVs are isolated by hydrostatic filtration dialysis (HFD) and treated with a defined solution of urea to optimize release of uEVs from sample. Presence of uEVs is confirmed by transmission electron microscopy, Western blotting, and proteomic profiling in MS. Results Using HFD with urea treatment for uEV isolation reduces sample complexity to a great extent. The novel simplified uEV isolation protocol allows comprehensive vesicle proteomics analysis and should be part of any urine analytics to release all sample constituents from THP trap. Conclusions and clinical relevance The method brings a quick and easy protocol for THP management during uEV isolation, providing major benefits for comprehensive sample analytics.Peer reviewe

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming to help users efficiently obtain information and execute tasks, and provide users with more intelligent, convenient, and rich interaction experiences. With the development of smartphones and IoT, computing and sensing devices have become ubiquitous, greatly expanding the boundaries of IPAs. However, due to the lack of capabilities such as user intent understanding, task planning, tool using, and personal data management etc., existing IPAs still have limited practicality and scalability. Recently, the emergence of foundation models, represented by large language models (LLMs), brings new opportunities for the development of IPAs. With the powerful semantic understanding and reasoning capabilities, LLM can enable intelligent agents to solve complex problems autonomously. In this paper, we focus on Personal LLM Agents, which are LLM-based agents that are deeply integrated with personal data and personal devices and used for personal assistance. We envision that Personal LLM Agents will become a major software paradigm for end-users in the upcoming era. To realize this vision, we take the first step to discuss several important questions about Personal LLM Agents, including their architecture, capability, efficiency and security. We start by summarizing the key components and design choices in the architecture of Personal LLM Agents, followed by an in-depth analysis of the opinions collected from domain experts. Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.Comment: https://github.com/MobileLLM/Personal_LLM_Agents_Surve

Treatment of complex limb fractures with 3D printing technology combined with personalized plates: a retrospective study of case series and literature review

BackgroundIn recent years, 3D printing technology has made significant strides in the medical field. With the advancement of orthopedics, there is an increasing pursuit of high surgical quality and optimal functional recovery. 3D printing enables the creation of precise physical models of fractures, and customized personalized steel plates can better realign and more comprehensively and securely fix fractures. These technologies improve preoperative diagnosis, simulation, and planning for complex limb fractures, providing patients with better treatment options.Patients and methodsFive typical cases were selected from a pool of numerous patients treated with 3D printing technology combined with personalized custom steel plates at our hospital. These cases were chosen to demonstrate the entire process of printing 3D models and customizing individualized steel plates, including details of the patients' surgeries and treatment procedures. Literature reviews were conducted, with a focus on highlighting the application of 3D printing technology combined with personalized custom steel plates in the treatment of complex limb fractures.Results3D printing technology can produce accurate physical models of fractures, and personalized custom plates can achieve better fracture realignment and more comprehensive and robust fixation. These technologies provide patients with better treatment options.ConclusionThe use of 3D printing models and personalized custom steel plates can improve preoperative diagnosis, simulation, and planning for complex limb fractures, realizing personalized medicine. This approach helps reduce surgical time, minimize trauma, enhance treatment outcomes, and improve patient functional recovery

A genome-wide association study of bronchodilator response in participants of European and African ancestry from six independent cohorts

Introduction Bronchodilator response (BDR) is a measurement of acute bronchodilation in response to short-acting β2-agonists, with a heritability between 10 and 40%. Identifying genetic variants associated with BDR may lead to a better understanding of its complex pathophysiology. Methods We performed a genome-wide association study (GWAS) of BDR in six adult cohorts with participants of European ancestry (EA) and African ancestry (AA) including community cohorts and cohorts ascertained on the basis of obstructive pulmonary disease. Validation analysis was carried out in two paediatric asthma cohorts. Results A total of 10 623 EA and 3597 AA participants were included in the analyses. No single nucleotide polymorphism (SNP) was associated with BDR at the conventional genome-wide significance threshold (p<5×10−8). Performing fine mapping and using a threshold of p<5×10−6 to identify suggestive variants of interest, we identified three SNPs with possible biological relevance: rs35870000 (within FREM1), which may be involved in IgE- and IL5-induced changes in airway smooth muscle cell responsiveness; rs10426116 (within ZNF284), a zinc finger protein, which has been implicated in asthma and BDR previously; and rs4782614 (near ATP2C2), involved in calcium transmembrane transport. Validation in paediatric cohorts yielded no significant SNPs, possibly due to age–genotype interaction effects. Conclusion Ancestry-stratified and ancestry-combined GWAS meta-analyses of over 14 000 participants did not identify genetic variants associated with BDR at the genome-wide significance threshold, although a less stringent threshold identified three variants showing suggestive evidence of association. A common definition and protocol for measuring BDR in research may improve future efforts to identify variants associated with BDR.publishedVersio

ChipNeMo: Domain-Adapted LLMs for Chip Design

ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: domain-adaptive tokenization, domain-adaptive continued pretraining, model alignment with domain-specific instructions, and domain-adapted retrieval models. We evaluate these methods on three selected LLM applications for chip design: an engineering assistant chatbot, EDA script generation, and bug summarization and analysis. Our evaluations demonstrate that domain-adaptive pretraining of language models, can lead to superior performance in domain related downstream tasks compared to their base LLaMA2 counterparts, without degradations in generic capabilities. In particular, our largest model, ChipNeMo-70B, outperforms the highly capable GPT-4 on two of our use cases, namely engineering assistant chatbot and EDA scripts generation, while exhibiting competitive performance on bug summarization and analysis. These results underscore the potential of domain-specific customization for enhancing the effectiveness of large language models in specialized applications.Comment: Updated results for ChipNeMo-70B mode

Omega-3 fatty acids and genome-wide interaction analyses reveal DPP10-pulmonary function association

Rationale: Omega-3 polyunsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health. Objective: To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility. Methods: Associations of n-3 PUFA biomarkers (a-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (FEV1, FVC, and FEV1/FVC) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N=16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N=11,962) and replicated in one cohort (N=1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of SNPassociations and their interactions with n-3PUFAs. Results: DPA and DHA were positively associated with FEV1 and FVC (P < 0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P-2df = 9.4 x 10(-9) across discovery and replication cohorts). The rs11693320-A allele (frequency, similar to 80%) was associated with lower FVC (P-SNP = 2.1 x 10(-9); beta(SNP) = 2161.0 ml), and the association was attenuated by higher DHA levels (P-SNPxDHA interaction = 2.1x10(-7); beta(SNPxDHA interaction) = 36.2 ml). Conclusions: We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction

Systemic Markers of Lung Function and Forced Expiratory Volume in 1 Second Decline across Diverse Cohorts.

Rationale: Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by airway obstruction and accelerated lung function decline. Our understanding of systemic protein biomarkers associated with COPD remains incomplete. Objectives: To determine what proteins and pathways are associated with impaired pulmonary function in a diverse population. Methods: We studied 6,722 participants across six cohort studies with both aptamer-based proteomic and spirometry data (4,566 predominantly White participants in a discovery analysis and 2,156 African American cohort participants in a validation). In linear regression models, we examined protein associations with baseline forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC). In linear mixed effects models, we investigated the associations of baseline protein levels with rate of FEV1 decline (ml/yr) in 2,777 participants with up to 7 years of follow-up spirometry. Results: We identified 254 proteins associated with FEV1 in our discovery analyses, with 80 proteins validated in the Jackson Heart Study. Novel validated protein associations include kallistatin serine protease inhibitor, growth differentiation factor 2, and tumor necrosis factor-like weak inducer of apoptosis (discovery β = 0.0561, Q = 4.05 × 10-10; β  = 0.0421, Q = 1.12 × 10-3; and β = 0.0358, Q = 1.67 × 10-3, respectively). In longitudinal analyses within cohorts with follow-up spirometry, we identified 15 proteins associated with FEV1 decline (Q &lt; 0.05), including elafin leukocyte elastase inhibitor and mucin-associated TFF2 (trefoil factor 2; β = -4.3 ml/yr, Q = 0.049; β = -6.1 ml/yr, Q = 0.032, respectively). Pathways and processes highlighted by our study include aberrant extracellular matrix remodeling, enhanced innate immune response, dysregulation of angiogenesis, and coagulation. Conclusions: In this study, we identify and validate novel biomarkers and pathways associated with lung function traits in a racially diverse population. In addition, we identify novel protein markers associated with FEV1 decline. Several protein findings are supported by previously reported genetic signals, highlighting the plausibility of certain biologic pathways. These novel proteins might represent markers for risk stratification, as well as novel molecular targets for treatment of COPD