Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.

OBJECTIVE: The remodelling of gut mycobiome (ie, fungi) during pregnancy and its potential influence on host metabolism and pregnancy health remains largely unexplored. Here, we aim to examine the characteristics of gut fungi in pregnant women, and reveal the associations between gut mycobiome, host metabolome and pregnancy health. DESIGN: Based on a prospective birth cohort in central China (2017 to 2020): Tongji-Huaxi-Shuangliu Birth Cohort, we included 4800 participants who had available ITS2 sequencing data, dietary information and clinical records during their pregnancy. Additionally, we established a subcohort of 1059 participants, which included 514 women who gave birth to preterm, low birthweight or macrosomia infants, as well as 545 randomly selected controls. In this subcohort, a total of 750, 748 and 709 participants had ITS2 sequencing data, 16S sequencing data and serum metabolome data available, respectively, across all trimesters. RESULTS: The composition of gut fungi changes dramatically from early to late pregnancy, exhibiting a greater degree of variability and individuality compared with changes observed in gut bacteria. The multiomics data provide a landscape of the networks among gut mycobiome, biological functionality, serum metabolites and pregnancy health, pinpointing the link between Mucor and adverse pregnancy outcomes. The prepregnancy overweight status is a key factor influencing both gut mycobiome compositional alteration and the pattern of metabolic remodelling during pregnancy. CONCLUSION: This study provides a landscape of gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health, which lays the foundation of the future gut mycobiome investigation for healthy pregnancy.

Nuclear Magnetic Resonance-Based Metabolomics and Risk of CKD.

RATIONALE & OBJECTIVE: Chronic kidney disease (CKD) leads to lipid and metabolic abnormalities, but a comprehensive investigation of lipids, lipoprotein particles, and circulating metabolites associated with the risk of CKD has been lacking. We examined the associations of nuclear magnetic resonance (NMR)-based metabolomics data with CKD risk in the UK Biobank study. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: A total of 91,532 participants in the UK Biobank Study without CKD and not receiving lipid-lowering therapy. EXPOSURE: Levels of metabolites including lipid concentration and composition within 14 lipoprotein subclasses, as well as other metabolic biomarkers were quantified via NMR spectroscopy. OUTCOME: Incident CKD identified using ICD codes in any primary care data, hospital admission records, or death register records. ANALYTICAL APPROACH: Cox proportional hazards regression models were used to estimate hazard ratios and 95% confidence intervals. RESULTS: We identified 2,269 CKD cases over a median follow-up period of 13.1 years via linkage with the electronic health records. After adjusting for covariates and correcting for multiple testing, 90 of 142 biomarkers were significantly associated with incident CKD. In general, higher concentrations of very-low-density lipoprotein (VLDL) particles were associated with a higher risk of CKD whereas higher concentrations of high-density lipoprotein (HDL) particles were associated with a lower risk of CKD. Higher concentrations of cholesterol, phospholipids, and total lipids within VLDL were associated with a higher risk of CKD, whereas within HDL they were associated with a lower risk of CKD. Further, higher triglyceride levels within all lipoprotein subclasses, including all HDL particles, were associated with greater risk of CKD. We also identified that several amino acids, fatty acids, and inflammatory biomarkers were associated with risk of CKD. LIMITATIONS: Potential underreporting of CKD cases because of case identification via electronic health records. CONCLUSIONS: Our findings highlight multiple known and novel pathways linking circulating metabolites to the risk of CKD. PLAIN-LANGUAGE SUMMARY: The relationship between individual lipoprotein particle subclasses and lipid-related traits and risk of chronic kidney disease (CKD) in general population is unclear. Using data from 91,532 participants in the UK Biobank, we evaluated the associations of metabolites measured using nuclear magnetic resonance testing with the risk of CKD. We identified that 90 out of 142 lipid biomarkers were significantly associated with incident CKD. We found that very-low-density lipoproteins, high-density lipoproteins, the lipid concentration and composition within these lipoproteins, triglycerides within all the lipoprotein subclasses, fatty acids, amino acids, and inflammation biomarkers were associated with CKD risk. These findings advance our knowledge about mechanistic pathways that may contribute to the development of CKD.

Depth-of-field extended Fourier ptychographic microscopy without defocus distance priori.

Fourier ptychographic microscopy (FPM) provides a solution of high-throughput phase imaging. Thanks to its coherent imaging model, FPM has the capacity of depth-of-field (DOF) extension by simultaneously recovering the sample's transmittance function and pupil aberration, which contains a defocus term. However, existing phase retrieval algorithms (PRs) often struggle in the presence of a significant defocus. In this Letter, different PRs with embedded pupil recovery are compared, and the one based on the alternating direction multiplier method (ADMM-FPM) demonstrates promising potential for reconstructing highly defocused FPM images. Besides, we present a plug-and-play framework that integrates ADMM-FPM and total variation or Hessian denoiser for pupil function enhancement. Both simulations and experiments demonstrate that this framework enables robust reconstruction of defocused FPM images without any prior knowledge of defocus distance or sample characteristics. In experiments involving USAF 1951 targets and pathologic slides, ADMM-FPM combined with the Hessian denoiser successfully corrected the defocus up to approximately 200 µm, i.e., extending the DOF to 400 µm.

Linear-space-variant model for Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) needs to realize well-accepted reconstruction by image segmentation and discarding problematic data due to artifacts caused by vignetting. However, the imaging results have long suffered from uneven color blocks and the consequent digital stitching artifacts, failing to bring satisfying experiences to researchers and users over the past decade since the invention of FPM. In fact, the fundamental reason for vignetting artifacts lies in that the acquired data does not match the adopted linear-space-invariant (LSI) forward model, i.e., the actual object function is modulated by a quadratic phase factor during data acquisition, which has been neglected in the advancement of FPM. In this Letter, we rederive a linear-space-variant (LSV) model for FPM and design the corresponding loss function for FPM, termed LSV-FPM. Utilizing LSV-FPM for optimization enables the efficient removal of wrinkle artifacts caused by vignetting in the reconstruction results, without the need of segmenting or discarding images. The effectiveness of LSV-FPM is validated through data acquired in both 4f and finite conjugate single-lens systems.

Fourier ptychographic microscopy with adaptive resolution strategy.

Fourier ptychographic microscopy (FPM) is a method capable of reconstructing a high-resolution, wide field-of-view (FOV) image, where dark-field images provide the high-frequency information required for the iterative process. Theoretically, using more dark-field images can lead to results with higher resolution. However, the resolution required to clearly detect samples with different microscales varies. For certain samples, the limit resolution of the imaging system may exceed the one required to resolve the details. This suggests that simply increasing the number of dark-field images will not improve the recognition capability for such samples and may instead significantly increase the computational cost. To address this issue, this Letter proposes an adaptive resolution strategy that automatically assigns the resolution required for the sample. Based on a Tenengrad approach, this strategy determines the number of images required for reconstruction by evaluating a series of differential images among the reconstructions for a certain subregion and then efficiently completes the full-FOV reconstruction according to the determined resolution. We conducted the full-FOV reconstruction utilizing feature-domain FPM for both the USAF resolution test chart and a human red blood cell sample. Employing the adaptive resolution strategy, the preservation of reconstruction resolution can be ensured while respectively economizing approximately 76% and 89% of the time.

Maternal overweight and obesity modify the association of serum fibroblast growth factor 21 levels with gestational diabetes mellitus: A nested case-control study.

AIMS: To examine the prospective association between fibroblast growth factor 21 (FGF21) and risk of gestational diabetes mellitus (GDM) and the modifying effect of overweight/obesity for this association. METHODS: Serum FGF21 levels were measured at 6-15 weeks of gestation among 332 GDM cases and 664 matched controls. Conditional logistic regression was used to evaluate its association with GDM risk. Interaction analyses on multiplicative and additive scales were conducted to investigate the modifying effect of overweight/obesity. RESULTS: Elevated FGF21 levels were associated with a higher risk of GDM in multivariable models, but the positive association was attenuated after further adjustment for pre-pregnancy body mass index (BMI). A significant multiplicative interaction was noted between FGF21 (both continuous and dichotomous) and pre-pregnancy BMI (p for interaction = 0.049 and 0.03), and the association was only significant in participants with pre-pregnancy BMI ≥24 kg/m2 . When participants were grouped based on pre-pregnancy BMI (≥24 and <24 kg/m2 ) and FGF21 levels (≥median and

APOE Genotype Modifies the Association between Midlife Adherence to the Planetary Healthy Diet and Cognitive Function in Later Life among Chinese Adults in Singapore.

BACKGROUND: It remains unclear if adherence to the planetary healthy diet (PHD), designed to improve human and environmental health, is associated with better cognitive function in aging, and if this association differs by apolipoprotein E (APOE) genotype. OBJECTIVES: We aimed to examine the association between the PHD pattern and risk of poor cognitive function, and to further assess whether the APOE ε4 allele could modify this association. METHODS: The study included 16,736 participants from the Singapore Chinese Health Study. The PHD score was calculated using data from a validated 165-item food frequency questionnaire at baseline (1993-1998), with higher scores indicating greater adherence to the PHD. Cognitive function was assessed by the Singapore-modified Mini-Mental State Examination at follow-up 3 visits (2014-2016). A subset of 9313 participants had APOE genotype data. Logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment for potential confounders. RESULTS: We identified 2397 (14.3%) cases of poor cognitive function. In the total population, OR (95% CI) of poor cognitive function for each one-SD increment in the PHD score was 0.89 (0.85, 0.93). Carriers of APOE ε4 allele had increased risk of poor cognitive function (OR: 1.36, 95% CI: 1.15, 1.61). There was a significant interaction between the PHD score and the APOE ε4 allele (P-interaction = 0.042). Each one-SD increment in the PHD score was significantly associated with lower risk of poor cognitive function (OR: 0.89; 95% CI: 0.83, 0.96) in non-carriers of APOE ε4 allele, but not in APOE ε4 allele carriers (OR: 1.04, 95% CI: 0.89, 1.23). CONCLUSIONS: Midlife adherence to the PHD was associated with reduced risk of poor cognitive function in later life. However, this was not observed in carriers of APOE ε4 allele who had higher risk of poor cognitive function.

Associations of Lower-Carbohydrate and Lower-Fat Diets with Mortality among People with Cardiovascular Disease.

BACKGROUND: Although low-carbohydrate and low-fat diets have been shown to have short-term metabolic benefits, the associations of these dietary patterns, particularly different food sources and macronutrient quality, with mortality in people with cardiovascular disease (CVD) remain unclear. OBJECTIVES: To examine the associations of different types of lower-carbohydrate diets (LCDs) and lower-fat diets (LFDs) with mortality in individuals with CVD. METHODS: This study included 3971 adults with CVD from the NHANES 1999-2014. Mortality status was linked to National Death Index mortality data through 31 December 2019. Overall, unhealthy and healthy LCD and LFD scores were determined based on the percentages of energy from total and subtypes of carbohydrate, fat, and protein. Cox proportional hazards regression models were applied to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Higher healthy LCD score was associated with favorable blood lipids and higher homeostasis model assessment of insulin resistance, whereas higher unhealthy LFD score was associated with lower high-density lipoprotein and higher C-reactive protein at baseline (all P-trend < 0.05). During 35,150 person-years of follow-up, 2163 deaths occurred. For per 20-percentile increment in dietary scores, the multivariate-adjusted HRs of all-cause mortality were 0.91 (95% CI: 0.86, 0.96) for healthy LCD score (P < 0.001), 0.94 (95% CI: 0.89, 1.00) for healthy LFD score (P = 0.04), and 1.07 (95% CI: 1.00, 1.14) for unhealthy LFD score (P = 0.04). CONCLUSIONS: Overall LCD and LFD scores are not associated with total mortality. Unhealthy LFD scores are associated with higher total mortality, whereas healthy LCD and LFD scores are associated with lower mortality in people with CVD.

Trends in cardiovascular health metrics and associations with long-term mortality among US adults with coronary heart disease.

BACKGROUND AND AIMS: Our study examined the trends of cardiovascular health metrics in individuals with coronary heart disease (CHD) and their associations with all-cause and cardiovascular disease mortality in the US. METHODS AND RESULTS: The cohort study was conducted based on the National Health and Nutrition Examination Survey 1999-2018 and their linked mortality files (through 2019). Baseline CHD was defined as a composite of self-reported doctor-diagnosed coronary heart disease, myocardial infarction, and angina pectoris. Cardiovascular health metrics were assessed according to the American Heart Association recommendations. Long-term all-cause and cardiovascular disease mortality were the primary outcomes. Survey-adjusted Cox regression models were used to estimate hazard ratios and corresponding 95% confidence intervals for the associations between cardiovascular health metrics and all-cause and cardiovascular disease mortality. The prevalence of one or fewer ideal cardiovascular health metrics increased from 14.15% to 22.79% (P < 0.001) in CHD, while the prevalence of more than four ideal cardiovascular health metrics decreased from 21.65% to 15.70 % (P < 0.001) from 1999 to 2018, respectively. Compared with CHD participants with one or fewer ideal cardiovascular health metrics, those with four or more ideal cardiovascular health metrics had a 35% lower risk (hazard ratio, 0.65; 95% confidence interval: 0.51, 0.82) and a 44% lower risk (0.56; 0.38, 0.84) in all-cause and cardiovascular disease mortality, respectively. CONCLUSION: Substantial declines were noted in ideal cardiovascular health metrics in US adults with CHD. A higher number of cardiovascular health metrics was associated with lower all-cause and cardiovascular disease mortality in them.

Circulating concentrations of bile acids and prevalent chronic kidney disease among newly diagnosed type 2 diabetes: a cross-sectional study.

BACKGROUND: The relationship between circulating bile acids (BAs) and kidney function among patients with type 2 diabetes is unclear. We aimed to investigate the associations of circulating concentrations of BAs, particularly individual BA subtypes, with chronic kidney disease (CKD) in patients of newly diagnosed type 2 diabetes. METHODS: In this cross-sectional study, we included 1234 newly diagnosed type 2 diabetes who participated in an ongoing prospective study, the Dongfeng-Tongji cohort. Circulating primary and secondary unconjugated BAs and their taurine- or glycine-conjugates were measured using ultraperformance liquid chromatography-tandem mass spectrometry. CKD was defined as eGFR < 60 ml/min per 1.73 m2. Logistic regression model was used to compute odds ratio (OR) and 95% confidence interval (CI). RESULTS: After adjusting for multiple testing, higher levels of total primary BAs (OR per standard deviation [SD] increment: 0.78; 95% CI: 0.65-0.92), cholate (OR per SD: 0.78; 95% CI: 0.66-0.92), chenodeoxycholate (OR per SD: 0.81; 95% CI: 0.69-0.96), glycocholate (OR per SD: 0.81; 95% CI: 0.68-0.96), and glycochenodeoxycholate (OR per SD: 0.82; 95% CI: 0.69-0.97) were associated with a lower likelihood of having CKD in patients with newly diagnosed type 2 diabetes. No significant relationships between secondary BAs and odds of CKD were observed. CONCLUSIONS: Our findings showed that higher concentrations of circulating unconjugated primary BAs and their glycine-conjugates, but not taurine-conjugates or secondary BAs, were associated with lower odds of having CKD in patients with type 2 diabetes.

Association of urinary and seminal plasma vanadium concentrations with semen quality: A repeated-measures study of 1135 healthy men.

Although animal studies have shown the reproductive toxicity of vanadium, less is known about its effects on semen quality in humans. Among 1135 healthy men who were screened as potential semen donors, we investigated the relationships of semen quality with urinary and seminal plasma vanadium levels via inductively coupled plasma-mass spectrometry (ICP-MS). Spearman rank correlation tests and linear regression models were used to assess the correlations between average urinary and within-individual pooled seminal plasma vanadium concentrations (n = 1135). We utilized linear mixed-effects models to evaluate the associations of urinary and seminal plasma vanadium levels (n = 1135) with repeated sperm quality parameters (n = 5576). Seminal plasma vanadium concentrations were not significantly correlated with urinary vanadium concentrations (r = 0.03). After adjusting for possible confounders, we observed inverse relationships of within-individual pooled seminal plasma vanadium levels with total count, semen volume, and sperm concentration (all P values for trend < 0.05). Specifically, subjects in the highest (vs. lowest) tertile of seminal plasma vanadium concentrations had - 11.3% (-16.4%, -5.9%), - 11.1% (-19.1%, -2.4%), and - 20.9% (-29.0%, -11.8%) lower sperm volume, concentration, and total count, respectively; moreover, urinary vanadium levels appeared to be negatively associated with sperm motility. These relationships showed monotonically decreasing dose-response patterns in the restricted cubic spline analyses. Our results demonstrated a poor correlation between urinary and seminal plasma levels of vanadium, and elevated vanadium concentrations in urine and seminal plasma may be adversely related to male semen quality.

Lipidomics in gestational diabetes mellitus.

PURPOSE OF REVIEW: Epidemiological and mechanistic studies have reported relationships between blood lipids, mostly measured by traditional method in clinical settings, and gestational diabetes mellitus (GDM). Recent advances of high-throughput lipidomics techniques have made available more comprehensive lipid profiling in biological samples. This review aims to summarize evidence from prospective studies in assessing relations between blood lipids and GDM, and discuss potential underlying mechanisms. RECENT FINDINGS: Mass spectrometry and nuclear magnetic resonance spectroscopy-based analytical platforms are extensively used in lipidomics research. Epidemiological studies have identified multiple novel lipidomic biomarkers that are associated with risk of GDM, such as certain types of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, cholesterol, and lipoproteins. However, the findings are inconclusive mainly due to the heterogeneities in study populations, sample sizes, and analytical platforms. Mechanistic evidence indicates that abnormal lipid metabolism may be involved in the pathogenesis of GDM by impairing pancreatic ß-cells and inducing insulin resistance through several etiologic pathways, such as inflammation and oxidative stress. SUMMARY: Lipidomics is a powerful tool to study pathogenesis and biomarkers for GDM. Lipidomic biomarkers and pathways could help to identify women at high risk for GDM and could be potential targets for early prevention and intervention of GDM.

Healthy lifestyle behaviors, mediating biomarkers, and risk of microvascular complications among individuals with type 2 diabetes: A cohort study.

BACKGROUND: The influence of overall lifestyle behaviors on diabetic microvascular complications remains unknown. In addition, the potential mediating biomarkers underlying the association is unclear. This study aimed to examine the associations of the combined lifestyle factors with risks of total and individual microvascular complications among patients with type 2 diabetes (T2D) and to explore the potential mediation effects of metabolic biomarkers. METHODS AND FINDINGS: This retrospective cohort study included 15,104 patients with T2D free of macro- and microvascular complications at baseline (2006 to 2010) from the UK Biobank. Healthy lifestyle behaviors included noncurrent smoking, recommended waist circumference, regular physical activity, healthy diet, and moderate alcohol drinking. Outcomes were ascertained using electronic health records. Over a median of 8.1 years of follow-up, 1,296 cases of the composite microvascular complications occurred, including 558 diabetic retinopathy, 625 diabetic kidney disease, and 315 diabetic neuropathy, with some patients having 2 or 3 microvascular complications simultaneously. After multivariable adjustment for sociodemographic characteristics, history of hypertension, glycemic control, and medication histories, the hazard ratios (95% confidence intervals (CIs)) for the participants adhering 4 to 5 low-risk lifestyle behaviors versus 0 to 1 were 0.65 (0.46, 0.91) for diabetic retinopathy, 0.43 (0.30, 0.61) for diabetic kidney disease, 0.46 (0.29, 0.74) for diabetic neuropathy, and 0.54 (0.43, 0.68) for the composite outcome (all Ps-trend ≤0.01). Further, the population-attributable fraction (95% CIs) of diabetic microvascular complications for poor adherence to the overall healthy lifestyle (<4 low-risk factors) ranged from 25.3% (10.0%, 39.4%) to 39.0% (17.7%, 56.8%). In addition, albumin, HDL-C, triglycerides, apolipoprotein A, C-reactive protein, and HbA1c collectively explained 23.20% (12.70%, 38.50%) of the associations between overall lifestyle behaviors and total diabetic microvascular complications. The key limitation of the current analysis was the potential underreporting of microvascular complications because the cases were identified via electronic health records. CONCLUSIONS: Adherence to overall healthy lifestyle behaviors was associated with a significantly lower risk of microvascular complications in patients with T2D, and the favorable associations were partially mediated through improving biomarkers of glycemic control, systemic inflammation, liver function, and lipid profile.

Effects of Sample Dilution on Nuclear Magnetic Resonance-Derived Metabolic Profiles of Human Urine.

Traditionally, a relatively big urine volume (e.g., 500 µL) is used in nuclear magnetic resonance (NMR)-based human metabolomics, which is not feasible for studies with limited/precious samples. Although urine may be diluted before conventional high-throughput metabolomics analysis, the comprehensive effect of urine dilution on metabolic profiles is unknown. Here, for the first time, we systematically investigated the effect of urine dilution on 1H NMR metabolic profiles, by evaluating signal detectability, integration, signal-to-noise ratio (SNR), chemical shift (δ) and its variation, and signal overlapping of 47 metabolites in 10 volunteers. We observed significant linear changes along with increased dilution, including decreased integration and SNR, altered δ, decreased intersample variation of δ, and increased separation between overlapped signals, e.g., lactate and threonine, ß-d-glucose and an unassigned signal, and histidine and 3-methylhistidine. We further tested the 40% dilution level (i.e., employing 300 µL urine) in an epidemiological study containing 1018 pregnant women from the Tongji-Shuangliu Birth Cohort, showing acceptable detectability and chemical shift variability for most of the 47 metabolites profiled. It indicated that mild (e.g., 40%) dilution of human urine can largely preserve the high-abundance metabolites profiled, reduce intersample chemical shift variations, and increase separations of overlapped signals, which is an improvement of routine sample preparation methods in NMR-based metabolomics and is applicable for studies with limited urine volumes, including large-scale epidemiological studies.

Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women.

BACKGROUND: Liver plays an important role in maintaining glucose homeostasis. We aimed to examine the associations of liver enzymes and hepatic steatosis index (HSI, a reliable biomarker for non-alcoholic fatty liver disease) in early pregnancy with subsequent GDM risk, as well as the potential mediation effects of lipid metabolites on the association between HSI and GDM. METHODS: In a birth cohort, liver enzymes were measured in early pregnancy (6-15 gestational weeks, mean 10) among 6,860 Chinese women. Multivariable logistic regression was performed to examine the association between liver biomarkers and risk of GDM. Pearson partial correlation and least absolute shrinkage and selection operator (LASSO) regression were conducted to identify lipid metabolites that were significantly associated with HSI in a subset of 948 women. Mediation analyses were performed to estimate the mediating roles of lipid metabolites on the association of HSI with GDM. RESULTS: Liver enzymes and HSI were associated with higher risks of GDM after adjustment for potential confounders, with ORs ranging from 1.42 to 2.24 for extreme-quartile comparisons (false discovery rate-adjusted P-trend ≤0.005). On the natural log scale, each SD increment of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and HSI was associated with a 1.15-fold (95% CI: 1.05, 1.26), 1.10-fold (1.01, 1.20), 1.21-fold (1.10, 1.32), 1.15-fold (1.04, 1.27), and 1.33-fold (1.18, 1.51) increased risk of GDM, respectively. Pearson partial correlation and LASSO regression identified 15 specific lipid metabolites in relation to HSI. Up to 52.6% of the association between HSI and GDM risk was attributed to the indirect effect of the HSI-related lipid score composed of lipid metabolites predominantly from phospholipids (e.g., lysophosphatidylcholine and ceramides) and triacylglycerol. CONCLUSIONS: Elevated liver enzymes and HSI in early pregnancy, even within a normal range, were associated with higher risks of GDM among Chinese pregnant women. The association of HSI with GDM was largely mediated by altered lipid metabolism.

Humoral and cellular immunity of two-dose inactivated COVID-19 vaccination in Chinese children: A prospective cohort study.

Children are the high-risk group for COVID-19, and in need of vaccination. However, humoral and cellular immune responses of COVID-19 vaccine remain unclear in vaccinated children. To establish the rational immunization strategy of inactivated COVID-19 vaccine for children, the immunogenicity of either one dose or two doses of the vaccine in children was evaluated. A prospective cohort study of 322 children receiving inactivated COVID-19 vaccine was established in China. The baseline was conducted after 28 days of the first dose, and the follow-up was conducted after 28 days of the second dose. The median titers of receptor binding domain (RBD)-IgG, and neutralizing antibody (NAb) against prototype strain and Omicron variant after the second dose increased significantly compared to those after the first dose (first dose: 70.0, [interquartile range, 30.0-151.0] vs. second dose: 1261.0 [636.0-2060.0] for RBD-IgG; 2.5 [2.5-18.6] vs. 252.0 [138.6-462.1] for NAb against prototype strain; 2.5 [2.5-2.5] vs. 15.0 [7.8-26.5] for NAb against Omicron variant, all p < 0.05). The flow cytometry results showed that the first dose elicited SARS-CoV-2 specific cellular immunity, while the second dose strengthened SARS-CoV-2 specific IL-2+ or TNF-α+  monofunctional, IFN-γ+ TNF-α+  bifunctional, and IFN-γ- IL-2+ TNF-α+ multifunctional CD4+ T cell responses (p < 0.05). Moreover, SARS-CoV-2 specific memory T cells were generated after the first vaccination, including the central memory T cells and effector memory T cells. The present findings provide scientific evidence for the vaccination strategy of the inactive vaccines among children against COVID-19 pandemic.

Design of Fourier ptychographic illuminator for single full-FOV reconstruction.

Fourier ptychographic microscopy (FPM) is a spatial-temporal-modulation high-throughput imaging technique via a sequential angle-varied LED illumination. Therefore, the illuminator is one of the key components and the design of this illuminator is significant. However, because of the property of spherical wave, partial coherence, and aperture-induced vignetting, the acquired images must be processed in blocks first, and rely on parallel reconstruction via a graphics processing unit (GPU). The high cost makes it unappealing compared with commercial whole slide imaging system via a low-cost central processing unit (CPU). Especially, the vignetting severely destroys the space-invariant model and induces obvious artifacts in FPM, which is the most difficult problem. The conventional method is to divide the field of view (FOV) into many tiles and omit those imperfect images, which is crude and may discards low frequency information. In this paper, we reevaluated the conditions of vignetting in FPM. Through our analysis, the maximum side length of FOV is 0.759 mm for a single full-FOV reconstruction via a 4×/0.1 NA objective and a 4 mm spacing LED array in theory, while almost 1.0 mm can be achieved in practice due to the tolerance of algorithm. We found that FPM system can treat the vignetting coefficient Vf below 0.1 as brightfield images and Vf lager than 0.9 as darkfield images, respectively. We reported an optimized distribution for designing an illuminator without vignetting effect according to the off-the-shelf commercial products, which can reconstruct full FOV in one time via a CPU. By adjusting the distribution of LED units, the system could retrieve the object with the side length of FOV up to 3.8 mm for a single full-FOV reconstruction, which achieves the largest FOV that a typical 4×/0.1 NA objective with the field number of 22 mm can afford.

Redundant information model for Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) is a computational optical imaging technique that overcomes the traditional trade-off between resolution and field of view (FOV) by exploiting abundant redundant information in both spatial and frequency domains for high-quality image reconstruction. However, the redundant information in FPM remains ambiguous or abstract, which presents challenges to further enhance imaging capabilities and deepen our understanding of the FPM technique. Inspired by Shannon's information theory and extensive experimental experience in FPM, we defined the specimen complexity and reconstruction algorithm utilization rate and reported a model of redundant information for FPM to predict reconstruction results and guide the optimization of imaging parameters. The model has been validated through extensive simulations and experiments. In addition, it provides a useful tool to evaluate different algorithms, revealing a utilization rate of 24%±1% for the Gauss-Newton algorithm, LED Multiplexing, Wavelength Multiplexing, EPRY-FPM, and GS. In contrast, mPIE exhibits a lower utilization rate of 19%±1%.

Ultra-broadband 1 × 2 3 dB power splitter using a thin-film lithium niobate from 1.2 to 2 µm wave band.

The 3 dB power splitters are fundamental building blocks for integrated photonic devices. As data capacity requirements continue to rise, there is a growing interest in integrated devices that can accommodate multiple spectral bands, including the conventional O-, C-, and L-bands, and the emerging 2 µm band. Here we propose and experimentally demonstrate a 3 dB power splitter based on adiabatic mode evolution using a thin-film lithium niobate, with ultra-broadband operation bandwidth from 1200 to 2100 nm. The fabricated power splitter exhibits low insertion losses of 0.2, 0.16, and 0.53 dB for wavelengths at 1310, 1550, and 2000 nm, respectively. The measured 1 dB bandwidth covers 1260-1360, 1480-1640, and 1930-2030 nm, which we believe that the proposed device is capable of operating in both O-, C-, L-, and 2 µm bands.

Associations of Nut Consumption with All-Cause Mortality among Individuals with Type 2 Diabetes.

BACKGROUND: Nuts are energy-dense, high-fat foods, and whether nut consumption influences mortality risk among individuals with type 2 diabetes (T2D) remains unclear. OBJECTIVES: This study aimed to investigate the associations of nut consumption with all-cause mortality among adults with T2D and to further explore the potential mediation effects of cardiometabolic biomarkers. METHODS: The current analysis included 5090 US participants with T2D from the National Health and Nutrition Examination Survey (1999-2014). Cox proportional hazards models were conducted to estimate hazard ratio (HR) and 95% confidence interval (CI). RESULTS: After 35,632 person-y of follow-up, 1174 deaths were documented. Higher nut consumption was significantly associated with a lower risk of all-cause mortality among individuals with T2D. After multivariable adjustment including lifestyles and dietary factors, diabetes duration, and glycated hemoglobin, compared with participants who did not consume nuts, the HR (95% CI) for those who consumed nuts over 3.5 ounce equivalent (oz.eq)/wk was 0.64 (0.50, 0.82; P-trend < 0.001) for all-cause mortality. A linear dose-response relationship was observed between nut consumption and all-cause mortality among individuals with T2D (Poverall=0.004, Pnonlinearity=0.35). In substitution analyses, replacing one serving of red and processed meat, refined grains, eggs, and dairy foods with one serving of nuts was associated with a 18% to 22% lower risk of all-cause mortality. In addition, mediation analysis suggested that C-reactive protein and γ-glutamine transaminase explained 6.7% and 9.1% of the relationship between nut consumption with all-cause mortality, respectively. CONCLUSIONS: Higher nut consumption was significantly associated with lower all-cause mortality among individuals with T2D. These findings indicate a potential benefit of nut consumption in the prevention of premature death among individuals with T2D.