Peatland Wildfires Enhance Nitrogen-Containing Organic Compounds in Marine Aerosols over the Western Pacific.

Peatland wildfires contribute significantly to the atmospheric release of light-absorbing organic carbon, often referred to as brown carbon. In this study, we examine the presence of nitrogen-containing organic compounds (NOCs) within marine aerosols across the Western Pacific Ocean, which are influenced by peatland fires from Southeast Asia. Employing ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) in electrospray ionization (ESI) positive mode, we discovered that NOCs are predominantly composed of reduced nitrogenous bases, including CHN+ and CHON+ groups. Notably, the count of NOC formulas experiences a marked increase within plumes from peatland wildfires compared to those found in typical marine air masses. These NOCs, often identified as N-heterocyclic alkaloids, serve as potential light-absorbing chromophores. Furthermore, many NOCs demonstrate pyrolytic stability, engage in a variety of substitution reactions, and display enhanced hydrophilic properties, attributed to chemical processes such as methoxylation, hydroxylation, methylation, and hydrogenation that occur during emission and subsequent atmospheric aging. During the daytime atmospheric transport, aging of aromatic N-heterocyclic compounds, particularly in aliphatic amines prone to oxidation and reactions with amine, was observed. The findings underscore the critical role of peatland wildfires in augmenting nitrogen-containing organics in marine aerosols, underscoring the need for in-depth research into their effects on marine ecosystems and regional climatic conditions.

Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

The global regulation of c-di-GMP and cAMP in bacteria.

Nucleotide second messengers are highly versatile signaling molecules that regulate a variety of key biological processes in bacteria. The best-studied examples are cyclic AMP (cAMP) and bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP), which both act as global regulators. Global regulatory frameworks of c-di-GMP and cAMP in bacteria show several parallels but also significant variances. In this review, we illustrate the global regulatory models of the two nucleotide second messengers, compare the different regulatory frameworks between c-di-GMP and cAMP, and discuss the mechanisms and physiological significance of cross-regulation between c-di-GMP and cAMP. c-di-GMP responds to numerous signals dependent on a great number of metabolic enzymes, and it regulates various signal transduction pathways through its huge number of effectors with varying activities. In contrast, due to the limited quantity, the cAMP metabolic enzymes and its major effector are regulated at different levels by diverse signals. cAMP performs its global regulatory function primarily by controlling the transcription of a large number of genes via cAMP receptor protein (CRP) in most bacteria. This review can help us understand how bacteria use the two typical nucleotide second messengers to effectively coordinate and integrate various physiological processes, providing theoretical guidelines for future research.

Fine-tuning large language models for rare disease concept normalization.

OBJECTIVE: We aim to develop a novel method for rare disease concept normalization by fine-tuning Llama 2, an open-source large language model (LLM), using a domain-specific corpus sourced from the Human Phenotype Ontology (HPO). METHODS: We developed an in-house template-based script to generate two corpora for fine-tuning. The first (NAME) contains standardized HPO names, sourced from the HPO vocabularies, along with their corresponding identifiers. The second (NAME+SYN) includes HPO names and half of the concept's synonyms as well as identifiers. Subsequently, we fine-tuned Llama 2 (Llama2-7B) for each sentence set and conducted an evaluation using a range of sentence prompts and various phenotype terms. RESULTS: When the phenotype terms for normalization were included in the fine-tuning corpora, both models demonstrated nearly perfect performance, averaging over 99% accuracy. In comparison, ChatGPT-3.5 has only ∼20% accuracy in identifying HPO IDs for phenotype terms. When single-character typos were introduced in the phenotype terms, the accuracy of NAME and NAME+SYN is 10.2% and 36.1%, respectively, but increases to 61.8% (NAME+SYN) with additional typo-specific fine-tuning. For terms sourced from HPO vocabularies as unseen synonyms, the NAME model achieved 11.2% accuracy, while the NAME+SYN model achieved 92.7% accuracy. CONCLUSION: Our fine-tuned models demonstrate ability to normalize phenotype terms unseen in the fine-tuning corpus, including misspellings, synonyms, terms from other ontologies, and laymen's terms. Our approach provides a solution for the use of LLMs to identify named medical entities from clinical narratives, while successfully normalizing them to standard concepts in a controlled vocabulary.

Study on Dynamic Mechanical Properties of Sandwich Beam with Stepwise Gradient Polymethacrylimide (PMI) Foam Core under Low-Velocity Impact.

Different PMI foam materials of 52, 110, and 200 kg/m3 were used to design stepwise gradient cores to improve the impact resistance of the sandwich beam. The stepwise gradient core consists of three layers arranged in positive gradient, negative gradient, and sandwich-core (e.g., 200/52/200). These sandwich beams were subjected to the impact of a steel projectile under impact momentum of 10 to 20 kg·m/s, corresponding to impact energy in the range of 12.5 to 50 J. During the test, the impact force was recorded by an accelerometer, and the different failure modes were also obtained. Subsequently, the influence of the layer arrangement on the energy absorption and load transfer mechanism between the different layers was analyzed. The results showed that the top layer with a large density can improve the impact force, but the middle/bottom layer with a low density promoted specific energy absorption. Thus, based on these two points, the negative gradient core (200/110/52) had an excellent specific energy absorption because it can transfer and expand the area to bear the load layer by layer, which improved the energy absorption in each layer. Combined with the failure modes, the load transfer and deformation mechanisms between the layers were also discussed. The present work provided a valuable method to design an efficient lightweight sandwich structure in the protection field.

Ruthenium red alleviates post-resuscitation myocardial dysfunction by upregulating mitophagy through inhibition of USP33 in a cardiac arrest rat model.

Cardiac arrest (CA) remains a leading cause of death, with suboptimal survival rates despite efforts involving cardiopulmonary resuscitation and advanced life-support technology. Post-resuscitation myocardial dysfunction (PRMD) is an important determinant of patient outcomes. Myocardial ischemia/reperfusion injury underlies this dysfunction. Previous reports have shown that ruthenium red (RR) has a protective effect against cardiac ischemia-reperfusion injury; however, its precise mechanism of action in PRMD remains unclear. This study investigated the effects of RR on PRMD and analyzed its underlying mechanisms. Ventricular fibrillation was induced in rats, which were then subjected to cardiopulmonary resuscitation to establish an experimental CA model. At the onset of return of spontaneous circulation, RR (2.5 mg/kg) was administered intraperitoneally. Our study showed that RR improved myocardial function and reduced the production of oxidative stress markers such as malondialdehyde (MDA), glutathione peroxidase (GSSG), and reactive oxygen species (ROS) production. RR also helped maintain mitochondrial structure and increased ATP and GTP levels. Additionally, RR effectively attenuated myocardial apoptosis. Furthermore, we observed downregulation of proteins closely related to mitophagy, including ubiquitin-specific protease 33 (USP33) and P62, whereas LC3B (microtubule-associated protein light chain 3B) was upregulated. The upregulation of mitophagy may play a critical role in reducing myocardial injury. These results demonstrate that RR may attenuate PRMD by promoting mitophagy through the inhibition of USP33. These effects are likely mediated through diverse mechanisms, including antioxidant activity, apoptosis suppression, and preservation of mitochondrial integrity and energy metabolism. Consequently, RR has emerged as a promising therapeutic approach for addressing post-resuscitation myocardial dysfunction.

Converting OMOP CDM to phenopackets: A model alignment and patient data representation evaluation.

OBJECTIVE: This study aims to promote interoperability in precision medicine and translational research by aligning the Observational Medical Outcomes Partnership (OMOP) and Phenopackets data models. Phenopackets is an expert knowledge-driven schema designed to facilitate the storage and exchange of multimodal patient data, and support downstream analysis. The first goal of this paper is to explore model alignment by characterizing the common data models using a newly developed data transformation process and evaluation method. Second, using OMOP normalized clinical data, we evaluate the mapping of real-world patient data to Phenopackets. We evaluate the suitability of Phenopackets as a patient data representation for real-world clinical cases. METHODS: We identified mappings between OMOP and Phenopackets and applied them to a real patient dataset to assess the transformation's success. We analyzed gaps between the models and identified key considerations for transforming data between them. Further, to improve ambiguous alignment, we incorporated Unified Medical Language System (UMLS) semantic type-based filtering to direct individual concepts to their most appropriate domain and conducted a domain-expert evaluation of the mapping's clinical utility. RESULTS: The OMOP to Phenopacket transformation pipeline was executed for 1,000 Alzheimer's disease patients and successfully mapped all required entities. However, due to missing values in OMOP for required Phenopacket attributes, 10.2 % of records were lost. The use of UMLS-semantic type filtering for ambiguous alignment of individual concepts resulted in 96 % agreement with clinical thinking, increased from 68 % when mapping exclusively by domain correspondence. CONCLUSION: This study presents a pipeline to transform data from OMOP to Phenopackets. We identified considerations for the transformation to ensure data quality, handling restrictions for successful Phenopacket validation and discrepant data formats. We identified unmappable Phenopacket attributes that focus on specialty use cases, such as genomics or oncology, which OMOP does not currently support. We introduce UMLS semantic type filtering to resolve ambiguous alignment to Phenopacket entities to be most appropriate for real-world interpretation. We provide a systematic approach to align OMOP and Phenopackets schemas. Our work facilitates future use of Phenopackets in clinical applications by addressing key barriers to interoperability when deriving a Phenopacket from real-world patient data.

LRG1 promotes the apoptosis of pulmonary microvascular endothelial cells through KLK10 in chronic obstructive pulmonary disease.

INTRODUCTION: Cigarette smoking is one of the most important causes of COPD and could induce the apoptosis of pulmonary microvascular endothelial cells (PMVECs). The conditional knockout of LRG1 from endothelial cells reduced emphysema in mice. However, the mechanism of the deletion of LRG1 from endothelial cells rescued by cigarette smoke (CS) induced emphysema remains unclear. This research aimed to demonstrate whether LRG1 promotes the apoptosis of PMVECs through KLK10 in COPD. METHODS: Nineteen patients were divided into three groups: control non-COPD (n=7), smoker non-COPD (n=7), and COPD (n=5). The emphysema mouse model defined as the CS exposure group was induced by CS exposure plus cigarette smoke extract (CSE) intraperitoneal injection for 28 days. Primary PMVECs were isolated from the mouse by magnetic bead sorting method via CD31-Dynabeads. Apoptosis was detected by western blot and flow cytometry. RESULTS: LRG1 was increased in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. KLK10 was over-expressed in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. LRG1 promoted apoptosis in PMVECs. LRG1 knockdown reversed CSE-induced apoptosis in PMVECs. The mRNA and protein expression of KLK10 were increased after over-expressed LRG1 in PMVECs isolated from mice. Similarly, both the mRNA and protein levels of KLK10 were decreased after LRG1 knockdown in PMVECs. The result of co-immunoprecipitation revealed a protein-protein interaction between LRG1 and KLK10 in PMVECs. KLK10 promoted apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. KLK10 knockdown could reverse CSE-induced apoptosis in PMVECs. CONCLUSIONS: LRG1 promotes apoptosis via up-regulation of KLK10 in PMVECs isolated from mice. KLK10 promotes apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. There was a direct protein-protein interaction between LRG1 and KLK10 in PMVECs. Our novel findings provide insights into the understanding of LRG1/KLK10 function as a potential molecule in COPD.

Exploring the relationship between illness perception, self-management and quality of life among HIV-positive men who have sex with men.

AIMS: This study aimed to explore the mediating effect of self-management (SM) on the relationship between illness perception and quality of life (QOL) among Human immunodeficiency virus (HIV)-positive men who have sex with men (MSM). DESIGN: A cross-sectional study. METHODS: We explored the effect of illness perception and self-management on QOL using the multiple regression model. Moreover, we conducted a simple mediation analysis to examine the role of SM in the relationship between illness perception and QOL. In addition, a parallel mediation analysis was performed to investigate the differences in domains of SM on the relationship between illness perception and QOL. RESULTS: Among 300 Chinese HIV-positive MSM, the mean score of SM was 39.9 ± 6.97, with a range of 14.0-54.0. The higher score in SM indicated a higher level of HIV SM. SM was negatively related to illness perception (r = -0.47) while positively related to QOL (r = 0.56). SM partially mediated the relationship between illness perception and QOL, accounting for 25.3% of the total effect. Specifically, both daily self-management health practices and the chronic nature of the self-management domain played a parallel role in mediating the relationship between illness perception and QOL. CONCLUSION: Our study demonstrated that SM was a significant factor influencing QOL among HIV-positive MSM. Focusing on daily self-management health practices and the chronic nature of self-management could be the potential key targets for enhancing HIV self-management strategies. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study emphasized the role of SM in the well-being of HIV-positive MSM and underscored the importance of developing interventions that integrate SM strategies to improve QOL in this population. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Odontogenic and anti-inflammatory effects of magnesium-doped bioactive glass in vital pulp therapy.

This study aimed to investigate the effects of magnesium-doped bioactive glass (Mg-BG) on the mineralization, odontogenesis, and anti-inflammatory abilities of human dental pulp stem cells (hDPSCs). Mg-BG powders with different Mg concentrations were successfully synthesized via the sol-gel method and evaluated using X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, and transmission electron microscopy. Apatite formation was observed on the surfaces of the materials after soaking in simulated body fluid. hDPSCs were cultured with Mg-BG powder extracts in vitro, and no evident cytotoxicity was observed. Mg-BG induced alkaline phosphatase (ALP) expression and mineralization of hDPSCs and upregulated the expression of odontogenic genes, including those encoding dentin sialophosphoprotein, dentin matrix protein 1, ALP, osteocalcin, and runt-related transcription factor 2. Moreover, secretion of inflammatory cytokines (interleukin [IL]-4, IL-6, IL-8, and tumor necrosis factor-alpha) was substantially suppressed by Mg-BG. Collectively, the results of this study suggest that Mg-BG has excellent in vitro bioactivity and is a potential material for vital pulp therapy for inflamed pulps.

Quantification of the Heat-Related Risk and Burden of Hospitalizations for Cause-Specific Injuries and Contribution of Human-Induced Climate Change: A Time-Stratified Case-Crossover Study in China.

BACKGROUND: Although ambient temperature has been linked with injury incidence, there have been few nationwide studies to quantify the temperature-related risk and burden of cause-specific injury hospitalizations. Additionally, the impact of human-induced climate change to injury burden remains unknown. OBJECTIVES: Our objectives are to examine the associations between ambient temperature and injury hospitalizations from various causes and to quantify the contribution of human-induced warming to the heat-related burden. METHODS: We collected injury hospitalization data from a nationwide hospital-based registry in China during 2000-2019. Using a time-stratified case-crossover design, we investigated the associations between daily mean temperature (°C) and cause-specific injury hospitalizations. We also quantified the burden of heat-related injuries under the scenarios with and without anthropogenic forcing, using the Detection and Attribution Model Intercomparison Project to assess the contribution of human-induced warming. RESULTS: Our study included a total of 988,087 patients with hospitalization records for injuries. Overall, compared to the temperature at minimum risk of hospitalization (-12.1°C), the relative risk of hospitalization at extreme hot temperature (30.8°C, 97.5th percentile) was 1.18 [95% confidence interval (CI): 1.14, 1.22], with an approximately linear association between temperature and hospitalization. Vulnerability to heat-related injuries was more pronounced among males, young (<18 years of age) or middle-aged (45-64 years of age) individuals, and those living in the North. The heat-related attributable fraction increased from 23.2% in the 2000s to 23.6% in the 2010s, with a corresponding increase in the contribution of human-induced change over time. In the 2010s, the heat-related attributable fractions for specific causes of injury ranged from 12.4% to 54.4%, with human-induced change accounting for 6.7% to 10.6% of the burden. DISCUSSION: This nationwide study presents new evidence of significant associations between temperature and cause-specific injury hospitalizations in China and highlights the increasing contribution of human-induced warming to the injury burden. https://doi.org/10.1289/EHP14057.

Mechanistic insights into cardiovascular effects of ultrafine particle exposure: A longitudinal panel study.

BACKGROUND: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. OBJECTIVES: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. METHODS: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. RESULTS: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0-3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7-12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. DISCUSSION: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Dynamic Marine Atmospheric Corrosion Behavior of AZ91 Mg Alloy Sailing from Yellow Sea to Western Pacific Ocean.

In this work, the dynamic marine atmospheric corrosion behavior of AZ91 Mg alloy sailing from Yellow Sea to Western Pacific Ocean was studied. The corrosion rates were measured using the weight loss method. The microstructure, phase, and chemical composition of corroded samples were investigated by SEM, EDS, XRD, and XPS. The results show that the evolution of corrosion rates of AZ91 Mg alloy was divided into three stages: rapidly increasing during the first 3 months, then remaining stable for the next three months, and finally decreasing after 6 months. The annual corrosion rate of Mg alloy reached 32.50 µm/y after exposure for 12 months in a dynamic marine atmospheric environment, which was several times higher than that of the static field exposure tests. AZ91 magnesium alloy was mainly subjected to localized corrosion with more destructiveness to Mg parts, which is mainly due to the synergistic effect of high relative humidity, the high deposition rate of chloride ion, sulfur dioxide acidic gas produced by fuel combustion, and rapid temperature changes caused by the alternating changes in longitude and latitude during navigation. As the exposure time increased, the corrosion pits gradually increased and deepened. The maximum depth of the corrosion pit was 197 µm after 12 months of exposure, which is almost 6 times the average corrosion depth. This study provides scientific data support for the application of magnesium alloys in shipborne aircraft and electronic equipment. The results could provide guidance for the design of new magnesium alloys and development of anti-corrosion technologies.

Effects of Curing Defects in Adhesive Layers on Carbon Fiber-Quartz Fiber Bonded Joint Performance.

Due to their mechanical load-bearing and functional wave transmission, adhesively bonded joints of carbon fiber-quartz fiber composites have been widely used in the new generation of stealth aviation equipment. However, the curing defects, caused by deviations between the process environment and the setting parameters, directly affect the service performance of the joint during the curing cycle. Therefore, the thermophysical parameter evolution of adhesive films was analyzed via dynamic DSC (differential scanning calorimeter), isothermal DSC and TGA (thermal gravimetric analyzer) tests. The various prefabricating defects within the adhesive layer were used to systematically simulate the impacts of void defects on the tensile properties, and orthogonal tests were designed to clarify the effects of the curing process parameters on the joints' bonding performance. The results demonstrate that the J-116 B adhesive film starts to cure at a temperature of 160 °C and gradually forms a three-dimensional mesh-bearing structure. Furthermore, a bonding interface between the J-116 B adhesive film and the components to be connected is generated. When the curing temperature exceeds 200 °C, both the adhesive film and the resin matrix thermally degrade the molecular structure. The adhesive strength weakens with an increasing defect area ratio and number, remaining more sensitive to triangle, edge and penetration defects. By affecting the molecular structure of the adhesive film, the curing temperature has a significant impact on the bonding properties; when the curing degree is ensured, the curing pressure directly impacts the adhesive's performance by influencing the morphology, number and distribution of voids. Conversely, the heating rate and heat preservation time have minimal effects on the bonding performance.

A novel design of copper selenide/zinc selenide/Nitrogen-doped carbon derived from MOF for sulfadiazine adsorption: Performance and mechanism.

Herein, a novel copper selenide/zinc selenide/Nitrogen-doped carbon (Cu2Se/ZnSe/NC) sphere was constructed via a combination of cation exchange, selenization and carbonization approaches with zinc-based metal-organic frameworks (ZIF-8) as precursor for sulfadiazine (SDZ) removal. Compared with the ZnSe/NC, the defective Cu2Se/ZnSe interface in the optimizing Cu-ZnSe/NC2 sample caused a remarkably improved adsorption performance. Notably, the adsorption capacity of 129.32 mg/g was better than that of mostly reported adsorbents for SDZ. And the adsorption referred to multiple-layer physical-chemical process that was spontaneous and exothermic. Besides, the Cu-ZnSe/NC2 displayed fast adsorption equilibrium of about 20 min and significant anti-interference ability for inorganic ions. Specially, the adsorbent possessed excellent stability and reusability, which could also be applied for rhodamine B (RhB), methylene blue (MB), and methyl orange (MO) dyes removal. Ultimately, the charge redistribution of Cu2Se/ZnSe interface greatly contributes the superior adsorption performance for SDZ, in which electrostatic attraction occupied extremely crucial status as compared to π-π electron-donor-acceptor (π-π EDA) interaction and hydrogen bonding (H-bonding), as revealed by the density function theory (DFT) calculations and experimental results. This study can provide a guideline for design of high-efficient adsorbent with interfacial charge redistribution.

Higher ambient temperatures may worsen obstructive sleep apnea: A nationwide smartwatch-based analysis of 6.2 million person-days.

Obstructive sleep apnea (OSA) is a serious type of sleep disorder that can lead to cardiometabolic and neurocognitive diseases. We utilized smart device-based photoplethysmography technology to collect sleep data from the Chinese population from 2019 to 2022. Distributed lag nonlinear models combined with a generalized nonlinear model or a linear mixed effects model were used to investigate the short-term associations between daily temperature and indicators of OSA severity. We included a total of 6,232,056 d of sleep monitoring data from 51,842 participants with moderate to severe risk of OSA from 313 Chinese cities. The relationships between ambient temperature and OSA exacerbation, apnea-hypopnea index (AHI), and minimum oxygen saturation (MinSpO2) were almost linear and present only on the same day. Higher temperatures were associated with a greater risk of OSA exacerbation, with an 8.4% (95% confidence interval (CI): 7.6%-9.3%) increase per 10 °C increase in temperature. A 10 °C increase in daily temperature corresponded to an AHI increase of 0.70 events h-1 (95% CI: 0.65-0.76) and a MinSpO2 decrease of 0.18% (95% CI: 0.16%-0.19%). Exposure to elevated temperatures during the night can also lead to adverse effects. The effects of higher temperatures on OSA severity were stronger among men, participants with a body mass index ≥24 kg m-2, those aged 45 years and older, individuals with a history of hypertension and diabetes, and during the cold season. This large-scale, nationwide, longitudinal study provides robust evidence suggesting that higher ambient temperatures may immediately worsen OSA.

Aplp1 interacts with Lag3 to facilitate transmission of pathologic α-synuclein.

Pathologic α-synuclein (α-syn) spreads from cell-to-cell, in part, through binding to the lymphocyte-activation gene 3 (Lag3). Here we report that amyloid ß precursor-like protein 1 (Aplp1) interacts with Lag3 that facilitates the binding, internalization, transmission, and toxicity of pathologic α-syn. Deletion of both Aplp1 and Lag3 eliminates the loss of dopaminergic neurons and the accompanying behavioral deficits induced by α-syn preformed fibrils (PFF). Anti-Lag3 prevents the internalization of α-syn PFF by disrupting the interaction of Aplp1 and Lag3, and blocks the neurodegeneration induced by α-syn PFF in vivo. The identification of Aplp1 and the interplay with Lag3 for α-syn PFF induced pathology deepens our insight about molecular mechanisms of cell-to-cell transmission of pathologic α-syn and provides additional targets for therapeutic strategies aimed at preventing neurodegeneration in Parkinson's disease and related α-synucleinopathies.

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts.

Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests and genetic tests, to find a possible answer over a prolonged period of time. Addressing this "diagnostic odyssey" thus has substantial clinical, psychosocial, and economic benefits. Many rare genetic diseases have distinctive facial features, which can be used by artificial intelligence algorithms to facilitate clinical diagnosis, in prioritizing candidate diseases to be further examined by lab tests or genetic assays, or in helping the phenotype-driven reinterpretation of genome/exome sequencing data. Existing methods using frontal facial photos were built on conventional Convolutional Neural Networks (CNNs), rely exclusively on facial images, and cannot capture non-facial phenotypic traits and demographic information essential for guiding accurate diagnoses. Here we introduce GestaltMML, a multimodal machine learning (MML) approach solely based on the Transformer architecture. It integrates facial images, demographic information (age, sex, ethnicity), and clinical notes (optionally, a list of Human Phenotype Ontology terms) to improve prediction accuracy. Furthermore, we also evaluated GestaltMML on a diverse range of datasets, including 528 diseases from the GestaltMatcher Database, several in-house datasets of Beckwith-Wiedemann syndrome (BWS, over-growth syndrome with distinct facial features), Sotos syndrome (overgrowth syndrome with overlapping features with BWS), NAA10-related neurodevelopmental syndrome, Cornelia de Lange syndrome (multiple malformation syndrome), and KBG syndrome (multiple malformation syndrome). Our results suggest that GestaltMML effectively incorporates multiple modalities of data, greatly narrowing candidate genetic diagnoses of rare diseases and may facilitate the reinterpretation of genome/exome sequencing data.