A Binuclear Metallohydrolase Model for RelA/SpoT-Homolog (RSH) Hydrolases.

When challenged by starvation, bacterial organisms synthesize guanosine penta- and tetraphosphate, collectively denoted as (p)ppGpp, as second messengers to reprogram metabolism towards slower growth and enhanced stress tolerance. When starvation is alleviated, the RelA-SpoT homolog (RSH) hydrolases down-regulate (p)ppGpp, cleaving the 3'-diphosphate to produce GTP or GDP. Metazoan RSH hydrolases (MESH) possess phosphatase activity responsible for converting cytoplasmic NADPH to NADH in mammalian cells. Inhibitor development for this family may therefore provide therapies to combat bacterial infection or metabolic dysregulation. Despite the availability of dozens of high-resolution structures, catalytic mechanisms of RSH hydrolases have remained poorly understood. All RSH hydrolases tightly bind a Mn2+ near its active center, which is believed sufficient for hydrolase activity. In contrast to this notion, we demonstrate, using the (p)ppGpp hydrolase SpoT from Acinetobacter baumannii, that a second divalent cation, presumably a Mg2+ under physiological conditions, is required for efficient catalysis. We also show that SpoT preferentially cleaves 3'-diphosphate over 3'-phosphate substrates, likely due to a key coordination between the ß-phosphate and the second metal center. MESH replaces this ß-phosphate with the side chain of an aspartate residue, thereby functioning as a phosphatase. We propose a binuclear metallohydrolase model where an invariant ED (Glu-Asp) diad, previously believed to activate the water nucleophile, instead coordinates to a Mg2+ center. The refined molecular and evolutionary blueprint of RSH hydrolases will provide a more reliable foundation for the development of small-molecule inhibitors of this important enzyme family.

Efficacy of COVID-19 Oral antivirals in hospitalised oldest-old with high morbidity burden: a target trial emulation study.

BACKGROUND: Molnupiravir and nirmatrelvir-ritonavir are orally administered pharmacotherapies for mild to moderate COVID-19. However, the effectiveness of these drugs among very old (≥80 years), hospitalised patients remains unclear, limiting the risk-benefit assessment of these antivirals in this specific group. This study investigates the effectiveness of these antivirals in reducing mortality among this group of hospitalised patients with COVID-19. METHODS: Using a territory-wide public healthcare database in Hong Kong, a target trial emulation study was conducted with data from 13 642 eligible participants for the molnupiravir trial and 9553 for the nirmatrelvir-ritonavir trial. The primary outcome was all-cause mortality. Immortal time and confounding bias was minimised using cloning-censoring-weighting approach. Mortality odds ratios were estimated by pooled logistic regression after adjusting confounding biases by stabilised inverse probability weights. RESULTS: Both molnupiravir (HR: 0.895, 95% CI: 0.826-0.970) and nirmatrelvir-ritonavir (HR: 0.804, 95% CI: 0.678-0.955) demonstrated moderate mortality risk reduction among oldest-old hospitalised patients. No significant interaction was observed between oral antiviral treatment and vaccination status. The 28-day risk of mortality was lower in initiators than non-initiators for both molnupiravir (risk difference: -1.09%, 95% CI: -2.29, 0.11) and nirmatrelvir-ritonavir (risk difference: -1.71%, 95% CI: -3.30, -0.16) trials. The effectiveness of these medications was observed regardless of the patients' prior vaccination status. CONCLUSIONS: Molnupiravir and nirmatrelvir-ritonavir are moderately effective in reducing mortality risk among hospitalised oldest-old patients with COVID-19, regardless of their vaccination status.

Recent advances in predicting acute mountain sickness: from multidimensional cohort studies to cutting-edge model applications.

High-altitude illnesses, encompassing a spectrum of health threats including Acute Mountain Sickness (AMS), pose significant challenges to individuals exposed to high altitude environments, necessitating effective prophylaxis and immediate management. Given the variability in individual responses to these conditions, accurate prediction of high-altitude illnesses onset is of paramount importance. This review systematically consolidates recent advancements in research on predicting AMS by evaluating existing cohort data, predictive models, and methodologies, while also delving into the application of emerging technologies. Through a thorough analysis of scholarly literature, we discuss traditional prediction methods anchored in physiological parameters (e.g., heart rate, respiratory frequency, blood pressure) and biochemical markers, as well as the integration and utility of novel technologies such as biosensors, genetic testing, and artificial intelligence within high-altitude prediction research. While conventional pre-diction techniques have been extensively used, they are often constrained by limitations in accuracy, reliability, and multifactorial influences. The advent of these innovative technologies holds promise for more precise individual risk assessments and personalized preventive and therapeutic strategies across various forms of AMS. Future research endeavors must pivot decisively towards the meticulous identification and stringent validation of innovative predictive biomarkers and models. This strategic re-direction should catalyze intensified interdisciplinary cooperation to significantly deepen our mechanistic insights into the pathogenesis of AMS while refining existing prediction methodologies. These groundbreaking advancements harbor the potential to fundamentally transform preventive and therapeutic frameworks for high-altitude illnesses, ultimately securing augmented safety standards and wellbeing for individuals operating at elevated altitudes with far-reaching global implications.

Comparative effectiveness and safety of BNT162b2 and CoronaVac in Hong Kong: A target trial emulation.

OBJECTIVES: To evaluate the difference between BNT162b2 and CoronaVac in vaccine effectiveness and safety. METHODS: This target trial emulation study included individuals aged ≥12 during 2022. Propensity score matching was applied to ensure group balance. The Cox proportional hazard model was used to compare the effectiveness outcomes including COVID-19 infection, severity, 28-day hospitalization, and 28-day mortality after infection. Poisson regression was used for safety outcomes including 32 adverse events of special interests between groups. RESULTS: A total of 639,818 and 1804,388 individuals were identified for the 2-dose and 3-dose comparison, respectively. In 2-dose and 3-dose comparison, the hazard ratios (95% confidence intervals [CI]) were 0.844 [0.833-0.856] and 0.749 [0.743-0.755] for COVID-19 infection, 0.692 [0.656-0.731] and 0.582 [0.559-0.605] for hospitalization, 0.566 [0.417-0.769] and 0.590 [0.458-0.76] for severe COVID-19, and 0.563 [0.456-0.697] and 0.457 [0.372-0.561] for mortality for BNT162b2 recipients versus CoronaVac recipients, respectively. Regarding safety, 2-dose BNT162b2 recipients had a significantly higher incidence of myocarditis (incidence rate ratio [IRR] [95% CI]: 8.999 [1.14-71.017]) versus CoronaVac recipients, but the difference was insignificant in 3-dose comparison (IRR [95% CI]: 2.000 [0.500-7.996]). CONCLUSION: BNT162b2 has higher effectiveness among individuals aged ≥12 against COVID-19-related outcomes for SARS-CoV-2 omicron compared to CoronaVac, with almost 50% lower mortality risk.

Age-specific Multimorbidity Patterns and Burden on All-Cause Mortality and Public Direct Medical Expenditure: A Retrospective Cohort Study.

OBJECTIVE: To evaluate age-specific multimorbidity patterns and morbidity burden on mortality and healthcare expenditure across age groups. PATIENTS AND METHODS: Retrospective observational study between January 1, 2009 to December 31, 2017 using electronic health records in Hong Kong: Individuals were stratified by age (< 50, 50-64, 65-79, ≥ 80), and sub-classified by number of morbidities (0, 1, 2, 3, ≥ 4) out of 21 common chronic conditions. Clustering analyses were conducted to identify specific patterns of multimorbidity. Association between the number as well as combinations of morbidities and all-cause mortality and public expenditure was examined. RESULTS: 4,562,832 individuals with a median follow-up of 7 years were included. Mental disorders were the top morbidities among young individuals, while cardiovascular diseases were prevalent in the elderly. An increased number of morbidities was associated with a greater relative risk for mortality and medical expenditure, and this relationship was stronger among younger patients. Compared to individuals in the same age group without morbidity, the hazard ratios (HR; 95% CI) of all-cause mortality in patients aged < 50 and ≥ 80 with two comorbidities 3.81 (3.60-4.03) and 1.38 (1.36-1.40), respectively, which increased to 14.22 (9.87-20.47) and 2.20 (2.13-2.26), respectively, as the number of morbidities increased to ≥ 4. The stroke-hypertension cluster was shown to be associated with the highest HR of mortality 2.48 (2.43-2.53) among all identified clusters arising from the clustering analysis. CONCLUSION: Given the stronger association between multimorbidity and all-cause mortality and greater opportunity costs in younger populations, prevention and management of early-onset multimorbidity are warranted. (248 words).

Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy.

Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.

Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods.

Temperature sensitivity (Q10) of ecosystem respiration (Re) is a critical parameter for predicting global terrestrial carbon dynamics and its response to climate warming. However, the determination of Q10 has been controversial. In this study, we scrutinized the underpinnings of three mainstream methods to reveal their relationships in estimating Q10 for Re in the Heihe River Basin, northwest China. Specifically, these methods are Q10 estimated from the long-term method (Q10_long), short-term method (Q10_short), and the low-frequency (Q10_lf) and high-frequency (Q10_hf) signals decomposed by the singular spectrum analysis (SSA) method. We found that: 1) Q10_lf and Q10_long are affected by the confounding effects caused by non-temperature factors, and are 1.8 ± 0.3 and 1.7 ± 0.3, respectively. 2) The high-frequency signals of the SSA method and short-term method have consistent roles in removing the confounding effects. Both Q10_short and Q10_hf reflect the actual response of respiration to temperature. 3) Overall, Q10_long has a larger variability (1.7 ± 0.3) across different biomes, whereas Q10_short and Q10_hf show convergence (1.4 ± 0.2 and 1.3 ± 0.1, respectively). These results highlight the fact that Q10 can be overestimated by the long-term method, whereas the short-term method and high-frequency signals decomposed by the SSA method can obtain closer and convergent values after removing the confounding effects driven by non-temperature factors. Therefore, it is recommended to use the Q10 value estimated by the short-term method or high-frequency signals decomposed by the SSA method to predict carbon dynamics and its response to global warming in Earth system models.

SPDEF drives pancreatic adenocarcinoma progression via transcriptional upregulation of S100A16 and activation of the PI3K/AKT signaling pathway.

Pancreatic adenocarcinoma (PAAD) is a notably aggressive malignancy with limited treatment options and an unfavorable prognosis for patients. We aimed to investigate molecular mechanisms by which Sam's pointed domain-containing ETS transcription factor (SPDEF) exerts effects on PAAD progression. We analyzed differentially expressed genes (DEGs) and their integration with ETS family members using the The Cancer Genome Atlas (TCGA) database, hence identifying SPDEF as a core gene in PAAD. Kaplan-Meier survival analysis confirmed SPDEF's prognostic potential. In vitro experiments validated the association with cell proliferation and apoptosis, affecting pancreatic cancer cell dynamics. We detected increased SPDEF expression in PAAD tumor samples. Our in vitro studies revealed that SPDEF regulates mRNA and protein expression levels, and significantly affects cell proliferation. Moreover, SPDEF was associated with reduced apoptosis and enhanced cell migration and invasion. In-depth analysis of SPDEF-targeted genes revealed four crucial genes for advanced prognostic model, among which S100A16 was significantly correlated with SPDEF. Mechanistic analysis showed that SPDEF enhances the transcription of S100A16, which in turn enhances PAAD cell migration, proliferation, and invasion by activating the PI3K/AKT signaling pathway. Our study revealed the critical role of SPDEF in promoting PAAD by upregulating S100A16 transcription and stimulating the PI3K/AKT signaling pathway. This knowledge deepened our understanding of pancreatic cancer's molecular progression and unveiled potential therapeutic strategies targeting SPDEF-driven pathways.

Immune to temperature interference sensor of carbon dioxide gas concentration based on a single modified fiber Bragg grating.

In this study, a novel method that can detect carbon dioxide (CO2) concentration and realize temperature immunity based on only one fiber Bragg grating (FBG) is proposed. The outstanding contribution lies in solving the temperature crosstalk issue of FBG and ensuring the accuracy of detection results under the condition of anti-temperature interference. To achieve immunity to temperature interference without changing the initial structure of FBG, the optical fiber cladding of FBG and adjacent optical fiber cladding at both ends of FBG are modified by a polymer coating. Moreover, a universal immune temperature demodulation algorithm is derived. The experimental results demonstrate that the temperature response sensitivity of the improved FBG is controlled within the range of 0.00407 nm/°C. Compared with the initial FBG (the temperature sensitivity of the initial FBG is 0.04 nm/°C), it decreases by nearly 10 times. Besides, the gas response sensitivity of FBG reaches 1.6 pm/ppm and has overwhelmingly ideal linearity. The detection error results manifest that the gas concentration error in 20 groups of data does not exceed 3.16 ppm. The final reproducibility research shows that the difference in detection sensitivity between the two sensors is 0.08 pm/ppm, and the relative error of linearity is 1.07%. In a word, the proposed method can accurately detect the concentration of CO2 gas and is efficiently immune to temperature interference. The sensor we proposed has the advantages of a simple production process, low cost, and satisfactory reproducibility. It also has the prospect of mass production.

Observation of Photoassociation Resonances in Ultracold Atom-Molecule Collisions.

We report on the observation of photoassociation resonances in ultracold collisions between ^{23}Na^{40}K molecules and ^{40}K atoms. We perform photoassociation in a long-wavelength optical dipole trap to form deeply bound triatomic molecules in electronically excited states. The atom-molecule Feshbach resonance is used to enhance the free-bound Franck-Condon overlap. The photoassociation into well-defined quantum states of excited triatomic molecules is identified by observing resonantly enhanced loss features. These loss features depend on the polarization of the photoassociation lasers, allowing us to assign rotational quantum numbers. The observation of ultracold atom-molecule photoassociation resonances paves the way toward preparing ground-state triatomic molecules, provides a new high-resolution spectroscopy technique for polyatomic molecules, and is also important to atom-molecule Feshbach resonances.

Data-Driven Controlled Synthesis of Oriented Quasi-Spherical CsPbBr3 Perovskite Materials.

Controlled synthesis of lead-halide perovskite crystals is challenging yet attractive because of the pivotal role played by the crystal structure and growth conditions in regulating their properties. This study introduces data-driven strategies for the controlled synthesis of oriented quasi-spherical CsPbBr3, alongside an investigation into the synthesis mechanism. High-throughput rapid characterization of absorption spectra and color under ultraviolet illumination was conducted using 23 possible ligands for the synthesis of CsPbBr3 crystals. The links between the absorption spectra slope (difference in the absorbance at 400 nm and 450 nm divided by a wavelength interval of 50 nm) and crystal size were determined through statistical analysis of more than 100 related publications. Big data analysis and machine learning were employed to investigate a total of 688 absorption spectra and 652 color values, revealing correlations between synthesis parameters and properties. Ex situ characterization confirmed successful synthesis of oriented quasi-spherical CsPbBr3 perovskites using polyvinylpyrrolidone and Acacia. Density functional theory calculations highlighted strong adsorption of Acacia on the (110) facet of CsPbBr3. Optical properties of the oriented quasi-spherical perovskites prepared with these data-driven strategies were significantly improved. This study demonstrates that data-driven controlled synthesis facilitates morphology-controlled perovskites with excellent optical properties.

Text analysis of Macao's COVID-19 prevention and control policies: discussion on strategy evolution and public health capabilities.

Background: The global impact of the coronavirus disease 2019 (COVID-19) pandemic has been profound. Macao Special Administrative Region (SAR), renowned as an international hub for tourism and entertainment, has actively responded to the crisis. However, a comprehensive analysis detailing the evolution of Macao SAR's policies throughout this period is currently lacking. Methods: This study aims to comprehensively understand the decision-making processes, policy formulation, and implementation strategies of the Macao SAR government amidst the pandemic through the analysis of speeches and inquiries made by legislative council members and other relevant documents. Employing both quantitative and qualitative analytical methods, including word frequency analysis and word vector models, we identify key themes and patterns. Additionally, we conducted a comparative analysis of keyword frequencies during the two waves of the pandemic using radar charts. Results: The results indicate a heightened focus by the Macao SAR government on pandemic control measures and economic impacts. In response, the government formulated and implemented policies, provided support initiatives, and managed port clearance, all while focusing on enhancing healthcare infrastructure and community services. Conclusions: The government persistently amends its policies in response to the evolving challenges posed by the pandemic. The evolution of the dynamic Zero-COVID strategy highlights the government's adaptability and comprehensive consideration, ensuring public health and societal stability.

Evolutionarily conserved Wnt/Sp5 signaling is critical for anterior-posterior axis patterning in sea urchin embryos.

Studies across a diverse group of metazoan embryos indicate that Wnt signaling often activates the transcription factor Sp5, forming a signaling 'cassette' that plays critical roles in many developmental processes. This study explores the role of Wnt/Sp5 signaling during the specification and patterning of the primary germ layers during early anterior-posterior axis formation in the deuterostome sea urchin embryo. Our functional analyses show that Sp5 is critical for endomesoderm specification downstream of Wnt/ß-catenin in posterior cells as well as anterior neuroectoderm patterning downstream of non-canonical Wnt/JNK signaling in anterior cells. Interestingly, expression and functional data comparisons show that Wnt/Sp5 signaling often plays similar roles in posterior endomesoderm as well as neuroectoderm patterning along the AP axis of several deuterostome embryos, including vertebrates. Thus, our findings provide strong support for the idea that Wnt-Sp5 signaling cassettes were critical for the establishment of early germ layers in the common deuterostome ancestor.

Synthetase and Hydrolase Specificity Collectively Excludes 2'-Deoxyguanosine from Bacterial Alarmone.

In response to starvation, virtually all bacteria pyrophosphorylate the 3'-hydroxy group of GTP or GDP to produce two messenger nucleotides collectively denoted as (p)ppGpp. Also known as alarmones, (p)ppGpp reprograms bacterial physiology to arrest growth and promote survival. Intriguingly, although cellular concentration of dGTP is two orders of magnitude lower than that of GTP, alarmone synthetases are highly selective against using 2'-deoxyguanosine (2dG) nucleotides as substrates. We thus hypothesize that production of 2dG alarmone, (p)pp(dG)pp, is highly deleterious, which drives a strong negative selection to exclude 2dG nucleotides from alarmone signaling. In this work, we show that the B. subtilis SasB synthetase prefers GDP over dGDP with 65,000-fold higher kcat/Km, a specificity stricter than RNA polymerase selecting against 2'-deoxynucleotides. Using comparative chemical proteomics, we found that although most known alarmone-binding proteins in Escherichia coli cannot distinguish ppGpp from pp(dG)pp, hydrolysis of pp(dG)pp by the essential hydrolase, SpoT, is 1,000-fold slower. This inability to degrade 2'-deoxy-3'-pyrophosphorylated substrate is a common feature of the alarmone hydrolase family. We further show that SpoT is a binuclear metallopyrophoshohydrolase and that hydrolysis of ppGpp and pp(dG)pp shares the same metal dependence. Our results support a model in which 2'-OH directly coordinates the Mn2+ at SpoT active center to stabilize the hydrolysis-productive conformation of ppGpp. Taken together, our study reveals a vital role of 2'-OH in alarmone degradation, provides new insight on the catalytic mechanism of alarmone hydrolases, and leads to the conclusion that 2dG nucleotides must be strictly excluded from alarmone synthesis because bacteria lack the key machinery to down-regulate such products.

Ammonia storage and slip under steady and transient state in close-coupled SCR.

The close-coupled selective catalytic reduction (cc-SCR) catalyst is an effective technology to reduce tailpipe NOx emission during cold start. This paper investigated the optimal ammonia storage under steady and transient state in the cc-SCR. The study showed that a trade-off between NOx conversion efficiency and ammonia slip is observed on the pareto solutions under steady state, and the optimal ammonia storage is calculated with ammonia slip less than 10 µL/L based on the China Ⅵ emission legislation. The rapid temperature increase will lead to severe ammonia slip in the transient test cycle. A simplified 0-D calculation method on ammonia slip under transient state is proposed based on kinetic model of ammonia adsorption and desorption. In addition, the effect of ammonia storage, catalyst temperature and temperature increasing rate on ammonia slip are analyzed. The optimal ammonia storage is calculated with maximum ammonia slip less than 100 µL/L according to the oxidation efficiency of ammonia slip catalyst (ASC) downstream cc-SCR. It was found that the optimal ammonia storage under transient state is much lower than that under steady state in cc-SCR at lower temperature, and a phase diagram is established to analyze the influence of temperature and temperature increasing rate on optimal ammonia storage.

Vaccine Effectiveness of BNT162b2 and CoronaVac against SARS-CoV-2 Omicron BA.2 in CKD.

BACKGROUND: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed increased risks of hospitalization and mortality in patients with underlying CKD. Current data on vaccine effectiveness of COVID-19 vaccines are limited to patients with CKD on dialysis and seroconversion in the non-dialysis population. METHODS: A case-control study was conducted of adults with CKD using data extracted from the electronic health record database in Hong Kong. Adults with CKD and COVID-19 confirmed by PCR were included in the study. Each case was matched with up to ten controls attending Hospital Authority services without a diagnosis of COVID-19 on the basis of age, sex, and index date (within three calendar days). The vaccine effectiveness of BNT162b2 and CoronaVac in preventing COVID-19 infection, hospitalizations, and all-cause mortality was estimated using conditional logistic regression adjusted by patients' comorbidities and medication history during the outbreak from January to March 2022. RESULTS: A total of 20,570 COVID-19 cases, 6604 COVID-19-related hospitalizations, and 2267 all-cause mortality were matched to 81,092, 62,803, and 21,348 controls, respectively. Compared with the unvaccinated group, three doses of BNT162b2 or CoronaVac were associated with a reduced risk of infection (BNT162b2: 64% [95% confidence interval (CI), 60 to 67], CoronaVac: 42% [95% CI, 38 to 47]), hospitalization (BNT162b2: 82% [95% CI, 77 to 85], CoronaVac: 80% [95% CI, 76 to 84]), and mortality (BNT162b2: 94% [95% CI, 88 to 97], CoronaVac: 93% [95% CI, 88 to 96]). Vaccines were less effective in preventing infection and hospitalization in the eGFR <15 and 15-29 ml/min per 1.73 m 2 subgroups as compared with higher GFR subgroups. However, receipt of vaccine, even for one dose, was effective in preventing all-cause mortality, with estimates similar to the higher eGFR subgroups, as compared with unvaccinated. CONCLUSIONS: A dose-response relationship was observed between the number of BNT162b2 or CoronaVac doses and the effectiveness against COVID-19 infection and related comorbidity in the CKD population.

Dose-response association of benzodiazepine use and development of deep vein thrombosis.

Benzodiazepines have sedative effects that cause reduced activity in users and may increase the risk of deep vein thrombosis. However, few studies have examined this potential risk of benzodiazepine use. This study examined the association between benzodiazepine use and the risk of deep vein thrombosis (DVT) in adults in Taiwan using a longitudinal health insurance database. The study population included 12,546 individuals with DVT and 50,184 matched controls. Results showed that benzodiazepine use was associated with an increased risk of DVT occurrence (adjusted odds ratio [aOR]: 1.66; 95 % CI, 1.54-1.79; P <0.001), with a dose-response relationship. Patients with a higher defined daily dose had a higher risk of DVT, with ORs of 1.65-, 2.09-, and 2.16-fold higher for those with an average benzodiazepine dose of <0.5, 0.5-0.9, or ≥1 (DDD/day), respectively, compared to nonbenzodiazepine users. Stratification by age, sex, and follow-up duration yielded similar results. This study highlights the need to evaluate the association and benefits of benzodiazepine prescription to decrease the risk of DVT development.

Association between BNT162b2 and CoronaVac vaccination and risk of CVD and mortality after COVID-19 infection: A population-based cohort study.

It is unknown if vaccination affects the risk of post-COVID-19 cardiovascular diseases (CVDs). Therefore, this retrospective cohort study examines the short-term and long-term risks of post-infection CVD among COVID-19 patients with different vaccination status utilizing data from electronic health databases in Hong Kong. Cox proportional hazards regression adjusted with inverse probability of treatment weighting is used to evaluate the risks of incident CVD (coronary heart disease, stroke, heart failure) and all-cause mortality in COVID-19 patients. Compared with unvaccinated patients, vaccinated patients have a lower risk of CVD and all-cause mortality, and the lowest risk is observed in those who completed three doses of vaccine. Similar patterns in the subgroups of different vaccine platforms, age, gender, Charlson comorbidity index, and disease severity are observed. These findings highlight a positive dose-response relationship between overall CVD risk reduction and the number of vaccine doses received.

Long-term effects of coronavirus disease 2019 on diabetes complications and mortality in people with diabetes: Two cohorts in the UK and Hong Kong.

AIM: To evaluate the long-term associations between coronavirus disease 2019 (COVID-19) and diabetes complications and mortality, in patients with diabetes. MATERIALS AND METHODS: People with diabetes diagnosed with COVID-19 infection (exposed group), from 16 March 2020 to 31 May 2021 from the UK Biobank (UKB cohort; n = 2456), and from 1 April 2020 to 31 May 2022 from the electronic health records in Hong Kong (HK cohort; n = 80 546), were recruited. Each patient was randomly matched with participants with diabetes but without COVID-19 (unexposed group), based on age and sex (UKB, n = 41 801; HK, n = 391 849). Patients were followed for up to 18 months until 31 August 2021 for UKB, and up to 28 months until 15 August 2022 for HK. Characteristics between cohorts were further adjusted with Inverse Probability Treatment Weighting. Long-term association of COVID-19 with multi-organ disease complications and all-cause mortality after 21 days of diagnosis was evaluated by Cox regression. RESULTS: Compared with uninfected participants, patients with COVID-19 infection with diabetes were consistently associated with higher risks of cardiovascular diseases (coronary heart disease [CHD]: hazard ratio [HR] [UKB]: 1.6 [95% confidence interval {CI}: 1.0, 2.4], HR [HK]: 1.2 [95% CI: 1.0, 1.5]; and stroke: HR [UKB]: 2.0 [95% CI: 1.1, 3.6], HR [HK]: 1.5 [95% CI: 1.3, 1.8]), microvascular disease (end stage renal disease: HR [UKB]: 2.1 [95% CI: 1.1, 4.0], HR [HK]: 1.2 [95% CI: 1.1, 1.4]) and all-cause mortality (HR [UKB]: 4.6 [95% CI: 3.8, 5.5], HR [HK]: 2.6 [95% CI: 2.5, 2.8]), in both cohorts. CONCLUSIONS: COVID-19 infection is associated with long-term increased risks of diabetes complications (especially cardiovascular complications, and mortality) in people with diabetes. Monitoring for signs/symptoms of developing these long-term complications post-COVID-19 infection in the infected patient population of people with diabetes may be beneficial in minimizing their morbidity and mortality.

A continuation method for image registration based on dynamic adaptive kernel.

Image registration is a fundamental problem in computer vision and robotics. Recently, learning-based image registration methods have made great progress. However, these methods are sensitive to abnormal transformation and have insufficient robustness, which leads to more mismatched points in the actual environment. In this paper, we propose a new registration framework based on ensemble learning and dynamic adaptive kernel. Specifically, we first use a dynamic adaptive kernel to extract deep features at the coarse level to guide fine-level registration. Then we added an adaptive feature pyramid network based on the integrated learning principle to realize the fine-level feature extraction. Through different scale, receptive fields, not only the local geometric information of each point is considered, but also its low texture information at the pixel level is considered. According to the actual registration environment, fine features are adaptively obtained to reduce the sensitivity of the model to abnormal transformation. We use the global receptive field provided in the transformer to obtain feature descriptors based on these two levels. In addition, we use the cosine loss directly defined on the corresponding relationship to train the network and balance the samples, to achieve feature point registration based on the corresponding relationship. Extensive experiments on object-level and scene-level datasets show that the proposed method outperforms existing state-of-the-art techniques by a large margin. More critically, it has the best generalization ability in unknown scenes with different sensor modes.