Contemporary Epidemiology, Management, and Outcomes of Patients Hospitalized for Heart Failure in China: Results From the China Heart Failure (China-HF) Registry.

BACKGROUND: Contemporary data on the epidemiology of heart failure (HF) in China are scarce. The China-HF Registry was designed to investigate clinical characteristics, management, and outcomes of patients hospitalized for HF in China. METHODS AND RESULTS: Data were collected prospectively on 13,687 patients with a primary discharge diagnosis of HF who were enrolled from 132 participating hospitals from January 2012 to September 2015. Data from the China-HF Registry was compared with previously published literature. The mean age was 65 ± 15 years, 59.1% were male, and 36.0% had preserved ejection fraction. Age, body mass index, and systolic blood pressure were lower than in high-income countries. Common comorbidities included hypertension (50.9%), coronary heart disease (49.6%), and atrial fibrillation (24.4%). The overall use of diuretics, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB), and ß-blockers at admission was 30.1%, 27.0%, and 25.6%, respectively, which was lower than in other registries. For patients discharged alive, ACEI/ARB, ß-blocker, and mineralocorticoid receptor antagonist use in patients with reduced ejection fraction was 67.5%, 70.0%, and 74.1%, respectively; device use was much lower. The median length of hospital stay was 10 (range 7-15) days, and in-hospital mortality was 4.1 ± 0.3%. Predictors of mortality included low systolic blood pressure, acute myocardial infarction, infection, right bundle branch block, and elevated total bilirubin and blood urea nitrogen level. CONCLUSIONS: Several important findings in patient profile and treatment patterns among Chinese patients with HF were noted compared with published literature. These data underscore the need for regional characterization of HF for global clinical trials and for the identification of several quality improvement opportunities.

Effect of angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers on cardiovascular events in patients with heart failure: a meta-analysis of randomized controlled trials.

BACKGROUND: Heart failure (HF) remains a significant cause of morbidity and mortality. Multiple trials over the past several years have examined the effects of both angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) in the treatment of left ventricular dysfunction, both acutely after myocardial infarction and in chronic heart failure. Yet, there is still confusion regarding the relative efficacy of rennin-angiotensin-aldosterone system (RAAS) inhibition. Our study was conducted to assess efficacy of ACEIs and ARBs in reducing all-cause and cardiovascular mortality in heart failure patients. METHODS: We included randomized clinical trials compared ACEIs and ARBs treatment (any dose or type) with placebo treatment, no treatment, or other anti-HF drugs treatment, reporting cardiovascular or total mortality with an observation period of at least 12 months. Data sources included Pubmed, EMBASE, the Cochrane Central Register of Controlled Trials. Dichotomous outcome data from individual trials were analyzed using the risk ratio measure and its 95%CI with random-effects/ fixed-effects models. We performed meta-regression analyses to identify sources of heterogeneity. All-cause mortality and CV mortality were thought to be the main outcomes. RESULTS: A total of 47,662 subjects were included with a mean/median follow-up ranged from 12 weeks to 4.5 years. Of all 38 studies, 32 compared ACEIs with control therapy (included 13 arms that compared ACEIs with placebo, 10 arms in which the comparator was active treatment and 9 arms that compared ACEIs with ARBs), and six studies compared ARBs with placebo. ACEIs treatment in patients with HF reduced all-cause mortality to 11% (risk ratio (RR): 0.89, 95% confidence interval (CI): 0.83-0.96, p = 0.001) and the corresponding value for cardiovascular mortality was 14% (RR: 0.86, 95% CI: 0.78-0.94, p = 0.001). However, ARBs had no beneficial effect on reducing all-cause and cardiovascular mortality. In head-to-head analysis, ACEIs was not superior to ARBs for all-cause mortality and cardiovascular deaths. CONCLUSIONS: In HF patients, ACEIs, but not ARBs reduced all-cause mortality and cardiovascular deaths. Thus, ACEIs should be considered as first-line therapy to limit excess mortality and morbidity in this population.

C/EBPB-CITED4 in Exercised Heart.

C/EBPB is a crucial transcription factor, participating in a variety of biological processes including cell proliferation, differentiation and development. In the cardiovascular system, C/EBPB-CITED4 signaling is known as a signaling pathway mediating exercise-induced cardiac growth. After its exact role in exercised heart firstly reported in 2010, more and more evidence confirmed that. MicroRNA (e.g. miR-222) and many molecules (e.g. Alpha-lipoic acid) can regulate this pathway and then involve in the cardiac protection effect induced by endurance exercise training. In addition, in cardiac growth during pregnancy, C/EBPB is also a required regulator. This chapter will give an introduction of the C/EBPB-CITED4 signaling and the regulatory network based on this signaling pathway in exercised heart.

ErbB4 Gene Polymorphism Is Associated With the Risk and Prognosis of Congestive Heart Failure in a Northern Han Chinese Population.

BACKGROUND: There has been no research evaluating the association between human Neuregulin (NRG) 1/ErbB2/ErbB4 gene polymorphisms and heart failure risk. METHODS AND RESULTS: Genotyping of 13 single nucleotide polymorphisms (SNPs) in the NRG-1/ErbB2/ErbB4 genes was performed in 569 unrelated heart failure patients and 682 healthy controls from a Northern Han Chinese population with the use of iPlex SNP Genotyping analysis on a Sequenom Massarray System. In the ErbB4 gene, the variants rs10932374 and rs1595064 were associated with reduced risk of heart failure under allelic, recessive and additive genetic models, and the variants rs13003941 and rs1595065 were associated with increased risk of heart failure under allelic, dominant, and additive models. The G-G-C-C-T haplotype of rs10932374-rs13003941-rs1595064-rs1595065-rs3748960 in the ErbB4 gene increased the risk of heart failure (odd ratio 1.35, 95% confidence interval [CI] 1.06-1.70; P = .014). The T variant of rs13003941 was associated with larger left ventricle (dominant model, P = .014; additive model, P = .048), and increased risk of overall death (relative risk [RR] 1.48, 95% CI 1.01-2.18; P = .045) and cardiovascular death (RR 1.56, 95% CI 1.04-2.33; P = .03) after adjusting for age and sex. NRG-1/ErbB2 gene polymorphisms were not associated with heart failure risk or prognosis. CONCLUSION: ErbB4 gene polymorphisms were associated with the risk, severity, and prognosis of heart failure in a Northern Han Chinese population.

[Reference value and clinical correlates of soluble ST2 in healthy community-based Chinese population].

OBJECTIVE: This study was designed to investigate the plasma level of soluble ST2 (sST2) and related influencing factors, and establish its reference value in the healthy community-based population in Beijing area of China. METHODS: We measured plasma sST2 level by enzyme-linked immunosorbent assay between March 2012 and August 2012 in 1 334 healthy subjects in communities, including 597 males and 737 females. Empiric and quantile regression methods were used to determine the reference range of plasma sST2. A multiple linear regression model was established to analyze the factors that might affect the level of plasma sST2. RESULTS: Gender is the most important factor affecting the plasma level of sST2 in healthy people. Plasma level of sST2 is significantly higher in men than in women (P < 0.01). Within each age strata, i.e. < 45, 45-54, 55-64, ≥ 65 years old, the plasma levels of sST2 were significantly higher in men than age-matched female (all P < 0.01). Age, body mass index (BMI), systolic blood pressure, diastolic blood pressure, and smoking did not affect plasma sST2 level. Reference range of sST2 was 5.7-53.5 µg/L for men and 4.4-42.4 µg/L for women (95% nonparametric reference interval). The one-side upper 95th percentile value of sST2 to discriminate the cardiovascular disease from healthy state was 47.2 µg/L for men and 37.2 µg/L for women. CONCLUSIONS: This study established the normal reference range of plasma sST2 in healthy community-based population. The major influencing factor of sST2 level in healthy population is gender.

Characterization of the complete mitochondrial genome of Spirobolus grahami (Diplopoda: Spirobolidae) with phylogenetic analysis.

Diplopoda is one of the most diverse and important groups of soil arthropods, but little research has been done on their phylogenetic relationship and evolution. Here, we sequenced and annotated the complete mitochondrial genomes of Spirobolus grahami. The total mitogenome of S. grahami was typical circular, double-stranded molecules, with 14,875 bp in length, including 13 protein-coding genes, 22 tRNAs, two rRNAs, and one control region. Base composition analysis suggested that the mitochondrial sequences were biased toward A and T, with A + T content of 58.68%. The mitogenomes of S. grahami exhibited negative AT and positive GC skews. Most of the 13 PCGs had ATN as the start codon, except COX1 start with CGA, and most PCGs ended with the T stop codon. The dN/dS values for most PCGs were lower than 1, suggesting that purifying selection was likely the main driver of mitochondrial PCG evolution. Phylogenetic analyses based on 13 PCGs using BI and ML methods support the classification of genus Spirobolus and Tropostreptus. Glomeridesmus spelaeus is distantly related to the other Diplopoda species.

All-optical complex field imaging using diffractive processors.

Complex field imaging, which captures both the amplitude and phase information of input optical fields or objects, can offer rich structural insights into samples, such as their absorption and refractive index distributions. However, conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a field. This limitation can be overcome using interferometric or holographic methods, often supplemented by iterative phase retrieval algorithms, leading to a considerable increase in hardware complexity and computational demand. Here, we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital processing. Our design utilizes successive deep learning-optimized diffractive surfaces that are structured to collectively modulate the input complex field, forming two independent imaging channels that perform amplitude-to-amplitude and phase-to-intensity transformations between the input and output planes within a compact optical design, axially spanning ~100 wavelengths. The intensity distributions of the output fields at these two channels on the sensor plane directly correspond to the amplitude and quantitative phase profiles of the input complex field, eliminating the need for any digital image reconstruction algorithms. We experimentally validated the efficacy of our complex field diffractive imager designs through 3D-printed prototypes operating at the terahertz spectrum, with the output amplitude and phase channel images closely aligning with our numerical simulations. We envision that this complex field imager will have various applications in security, biomedical imaging, sensing and material science, among others.

Information-hiding cameras: Optical concealment of object information into ordinary images.

We introduce an information-hiding camera integrated with an electronic decoder that is jointly optimized through deep learning. This system uses a diffractive optical processor, which transforms and hides input images into ordinary-looking patterns that deceive/mislead observers. This information-hiding transformation is valid for infinitely many combinations of secret messages, transformed into ordinary-looking output images through passive light-matter interactions within the diffractive processor. By processing these output patterns, an electronic decoder network accurately reconstructs the original information hidden within the deceptive output. We demonstrated our approach by designing information-hiding diffractive cameras operating under various lighting conditions and noise levels, showing their robustness. We further extended this framework to multispectral operation, allowing the concealment and decoding of multiple images at different wavelengths, performed simultaneously. The feasibility of our framework was also validated experimentally using terahertz radiation. This optical encoder-electronic decoder-based codesign provides a high speed and energy efficient information-hiding camera, offering a powerful solution for visual information security.

The First Complete Mitochondrial Genome of the Genus Litostrophus: Insights into the Rearrangement and Evolution of Mitochondrial Genomes in Diplopoda.

This study presents the complete mitochondrial genome (mitogenome) of Litostrophus scaber, which is the first mitogenome of the genus Litostrophus. The mitogenome is a circular molecule with a length of 15,081 bp. The proportion of adenine and thymine (A + T) was 69.25%. The gene ND4L used TGA as the initiation codon, while the other PCGs utilized ATN (A, T, G, C) as the initiation codons. More than half of the PCGs used T as an incomplete termination codon. The transcription direction of the L. scaber mitogenome matched Spirobolus bungii, in contrast to most millipedes. Novel rearrangements were found in the L. scaber mitogenome: trnQ -trnC and trnL1- trnP underwent short-distance translocations and the gene block rrnS-rrnL-ND1 moved to a position between ND4 and ND5, resulting in the formation of a novel gene order. The phylogenetic analysis showed that L. scaber is most closely related to S. bungii, followed by Narceus magnum. These findings enhance our understanding of the rearrangement and evolution of Diplopoda mitogenomes.

All-optical phase conjugation using diffractive wavefront processing.

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

Pyramid diffractive optical networks for unidirectional image magnification and demagnification.

Diffractive deep neural networks (D2NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational tasks between an input and output field-of-view. Here, we present a pyramid-structured diffractive optical network design (which we term P-D2NN), optimized specifically for unidirectional image magnification and demagnification. In this design, the diffractive layers are pyramidally scaled in alignment with the direction of the image magnification or demagnification. This P-D2NN design creates high-fidelity magnified or demagnified images in only one direction, while inhibiting the image formation in the opposite direction-achieving the desired unidirectional imaging operation using a much smaller number of diffractive degrees of freedom within the optical processor volume. Furthermore, the P-D2NN design maintains its unidirectional image magnification/demagnification functionality across a large band of illumination wavelengths despite being trained with a single wavelength. We also designed a wavelength-multiplexed P-D2NN, where a unidirectional magnifier and a unidirectional demagnifier operate simultaneously in opposite directions, at two distinct illumination wavelengths. Furthermore, we demonstrate that by cascading multiple unidirectional P-D2NN modules, we can achieve higher magnification factors. The efficacy of the P-D2NN architecture was also validated experimentally using terahertz illumination, successfully matching our numerical simulations. P-D2NN offers a physics-inspired strategy for designing task-specific visual processors.

All-optical image denoising using a diffractive visual processor.

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images - implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30-40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.

Phase 2 dose-ranging study to evaluate the efficacy and safety of liposomal irinotecan (LY01610) as a second-line treatment for patients with relapsed small cell lung cancer.

Background: This was a multicenter, single-arm dose-ranging phase 2 study aimed to assess the efficacy and safety of LY01610, a liposomal irinotecan, at various doses for patients with relapsed small cell lung cancer (SCLC). Methods: This study (NCT04381910) enrolled patients with relapsed SCLC at 10 hospitals across China, who have failed with previous platinum-based treatments. LY01610 was administered at doses of 60 mg/m2, 80 mg/m2, and 100 mg/m2. Primary endpoints were investigator-assessed objective response rate (ORR) and investigator-assessed duration of response (DoR). Secondary endpoints included investigator-assessed disease control rate (DCR), investigator-assessed progression-free survival (PFS), overall survival (OS), and safety. Findings: From September 3, 2020 to March 3, 2022, a total of 66 patients were enrolled, with 6, 30, and 30 allocated to the 60 mg/m2, 80 mg/m2, and 100 mg/m2 dose groups, respectively, with 68% (45/66) having a chemotherapy-free interval <90 days. In all 66 patients, the ORR was 32% (21/66, 95% confidence interval [CI], 21-44), with a median DoR of 5.2 months (95% CI, 3.0-8.3). Median PFS and OS were 4.0 (95% CI, 2.9-5.5) and 9.7 (95% CI, 7.2-12.3) months, respectively. The ORR of 60 mg/m2, 80 mg/m2, and 100 mg/m2 dose group were 33% (2/6), 33% (10/30), and 30% (9/30), respectively. The median DoR of 60 mg/m2, 80 mg/m2, and 100 mg/m2 dose group were 4.2 (95% CI, 2.8-not reached), 6.9 (95% CI, 2.5-9.9), and 4.0 (95% CI, 2.7-6.8) months, respectively. The incidence of ≥ grade 3 treatment-related adverse events (TRAEs) in the 60 mg/m2, 80 mg/m2, and 100 mg/m2 dose group were 33% (2/6), 47% (14/30), and 50% (15/30), respectively. The most common ≥ grade 3 TRAEs of all 66 patients were neutropenia (27%), leukopenia (24%) and anemia (15%). Interpretation: LY01610 exhibited promising clinical efficacy and manageable safety profiles in patients with relapsed SCLC, the 80 mg/m2 dose group had the best benefit-risk ratio. Funding: This study was supported by Luye Pharma Group Ltd.

Age-related changes in cellular electrophysiology and calcium handling for atrial fibrillation.

This study was to investigate whether or not the dysfunction of atrial repolarization and abnormality of the intracellular Ca(2+) handling protein was augmented with ageing. Four groups of dogs were studied, adult and aged dogs in sinus rhythm (SR) and atrial fibrillation (AF) induced by rapid atrial pacing. We used whole cell patch clamp recording techniques to measure L-type Ca(2+) current in cardiomyocytes dispersed from the left atria. Expressions of the Ca(2+) handling protein were measured by real-time quantitative reverse transcription-polymerase chain reaction and Western blot methods. Cardiomyocytes from old atria showed longer action potential (AP) duration to 90% repolarization, lower AP plateau potential and peak L-type Ca(2+) current densities at both age groups in SR. AF led to a higher maximum diastolic potential, an increase of amplitude of phase 0, decreases of AP duration to 90% repolarization, plateau potential and peak L-type Ca(2+) current densities. Compared to the adult group, mRNA and protein expressions of the L-type calcium channel a1c were decreased, whereas expressions of calcium adenosine triphosphatase were increased in the aged group. Compared to SR group, expressions of Ca(2+) handling protein except for phospholamban were significantly decreased in both age groups with AF. We conclude that these ageing-induced electrophysiological and molecular changes showed that general pathophysiological adaptations might provide a substrate conducive to AF.

[Association of single nucleotide polymorphism of KCNE1 and KCNE4 gene with atrial fibrillation in Xinjiang Uygur and Han population].

OBJECTIVE: To investigate the association between the KCNE1 gene G38S and the KCNE4 gene E145D and atrial fibrillation in Uygur and Han populations living in Xinjiang. METHODS: KCNE1 gene G38S and the KCNE4 gene E145D genotype and frequency were determined using PCR restriction fragment length polymorphism (PCR-RFLP) in 488 atrial fibrillation patients (237 Uygur and 251 Han residents) and 488 age-and-gender matched controls (237 Uygur and 251 Han residents). RESULTS: Genotype and allele frequency of KCNE1 gene G38S were similar between atrial fibrillation group and control group in the Han population (P = 0.556, P = 0.946). In the Uygur population, there was a statistical difference between atrial fibrillation group and control group (P = 0.018, P = 0.003). Logistic regression analysis revealed the KCNE1 38 G was one of the independent risk factors for atrial fibrillation in the Uygur population (OR = 1.634, 95%CI: 1.192-2.240, P = 0.002). The KCNE4 gene E145D, genotype and allele frequency were significantly different between atrial fibrillation group and control group in the Uygur population and Han population (P = 0.041, P = 0.015;P = 0.032, P = 0.013) . Logistic regression analysis revealed the KCNE4 145D was one of the independent risk factors for atrial fibrillation in the Uygur population and Han population (OR = 1.636, 95%CI:1.173-2.281, P = 0.004; OR = 1.491, 95%CI:1.076-2.065, P = 0.016) . CONCLUSIONS: KCNE1 G38S is not associated with atrial fibrillation in the Han population while the KCNE1 G38S is associated with atrial fibrillation in the Uygur population. KCNE4 gene E145D is associated with atrial fibrillation in both Uygur population and Han population.

Universal Polarization Transformations: Spatial Programming of Polarization Scattering Matrices Using a Deep Learning-Designed Diffractive Polarization Transformer.

Controlled synthesis of optical fields having nonuniform polarization distributions presents a challenging task. Here, a universal polarization transformer is demonstrated that can synthesize a large set of arbitrarily-selected, complex-valued polarization scattering matrices between the polarization states at different positions within its input and output field-of-views (FOVs). This framework comprises 2D arrays of linear polarizers positioned between isotropic diffractive layers, each containing tens of thousands of diffractive features with optimizable transmission coefficients. After its deep learning-based training, this diffractive polarization transformer can successfully implement Ni No = 10 000 different spatially-encoded polarization scattering matrices with negligible error, where Ni and No represent the number of pixels in the input and output FOVs, respectively. This universal polarization transformation framework is experimentally validated in the terahertz spectrum by fabricating wire-grid polarizers and integrating them with 3D-printed diffractive layers to form a physical polarization transformer. Through this set-up, an all-optical polarization permutation operation of spatially-varying polarization fields is demonstrated, and distinct spatially-encoded polarization scattering matrices are simultaneously implemented between the input and output FOVs of a compact diffractive processor. This framework opens up new avenues for developing novel devices for universal polarization control and may find applications in, e.g., remote sensing, medical imaging, security, material inspection, and machine vision.

Learning diffractive optical communication around arbitrary opaque occlusions.

Free-space optical communication becomes challenging when an occlusion blocks the light path. Here, we demonstrate a direct communication scheme, passing optical information around a fully opaque, arbitrarily shaped occlusion that partially or entirely occludes the transmitter's field-of-view. In this scheme, an electronic neural network encoder and a passive, all-optical diffractive network-based decoder are jointly trained using deep learning to transfer the optical information of interest around the opaque occlusion of an arbitrary shape. Following its training, the encoder-decoder pair can communicate any arbitrary optical information around opaque occlusions, where the information decoding occurs at the speed of light propagation through passive light-matter interactions, with resilience against various unknown changes in the occlusion shape and size. We also validate this framework experimentally in the terahertz spectrum using a 3D-printed diffractive decoder. Scalable for operation in any wavelength regime, this scheme could be particularly useful in emerging high data-rate free-space communication systems.

Data-Class-Specific All-Optical Transformations and Encryption.

Diffractive optical networks provide rich opportunities for visual computing tasks. Here, data-class-specific transformations that are all-optically performed between the input and output fields-of-view (FOVs) of a diffractive network are presented. The visual information of the objects is encoded into the amplitude (A), phase (P), or intensity (I) of the optical field at the input, which is all-optically processed by a data-class-specific diffractive network. At the output, an image sensor-array directly measures the transformed patterns, all-optically encrypted using the transformation matrices preassigned to different data classes, i.e., a separate matrix for each data class. The original input images can be recovered by applying the correct decryption key (the inverse transformation) corresponding to the matching data class, while applying any other key will lead to loss of information. All-optical class-specific transformations covering A → A, I → I, and P → I transformations using various image datasets are numerically demonstrated. The feasibility of this framework is also experimentally validated by fabricating class-specific I → I transformation diffractive networks and is successfully tested at different parts of the electromagnetic spectrum, i.e., 1550 nm and 0.75 mm wavelengths. Data-class-specific all-optical transformations provide a fast and energy-efficient method for image and data encryption, enhancing data security and privacy.

Unidirectional imaging using deep learning-designed materials.

A unidirectional imager would only permit image formation along one direction, from an input field-of-view (FOV) A to an output FOV B, and in the reverse path, B â†’ A, the image formation would be blocked. We report the first demonstration of unidirectional imagers, presenting polarization-insensitive and broadband unidirectional imaging based on successive diffractive layers that are linear and isotropic. After their deep learning-based training, the resulting diffractive layers are fabricated to form a unidirectional imager. Although trained using monochromatic illumination, the diffractive unidirectional imager maintains its functionality over a large spectral band and works under broadband illumination. We experimentally validated this unidirectional imager using terahertz radiation, well matching our numerical results. We also created a wavelength-selective unidirectional imager, where two unidirectional imaging operations, in reverse directions, are multiplexed through different illumination wavelengths. Diffractive unidirectional imaging using structured materials will have numerous applications in, e.g., security, defense, telecommunications, and privacy protection.

[Aging-related ionic remodeling of L-type voltage dependent calcium channel in left atria of canine].

OBJECTIVE: To investigate aging-related ionic remodeling of L-type voltage dependent calcium channel (LVDCC) in left atria of canine. METHODS: Seven adult (2.0 - 2.5 years) and 10 aged (> 8 years) dogs were used. The current of LVDCC was recorded by patch clamp technique in the whole cell mode. The action potential duration (APD(90)), amplitude of action potential plateau (APA), I(Ca-L) peak current density of LVDCC were recorded. The mRNA and protein expressions of α1c subunit (Ca(V1.2)), sarcoplasmic reticulum Ca(2+)-ATPase (SECRA(2)), Calpain-I, ryanodine receptor (RYR(2)) were detected by quantitative RT-PCR and Western blot, respectively. RESULTS: I(Ca-L) peak current density [(-8.11 ± 0.54) pA/pF vs. (-14.04 ± 0.82) pA/pF, P < 0.05] was significantly reduced and action potential duration to 90% repolarization (APD(90)) significantly prolonged [(340.5 ± 10.1) ms vs. (320.0 ± 7.9) ms, P < 0.05] in aged group than in adult group. The mRNA gene expression level of Ca(V1.2) was significantly lower (0.90 ± 0.35 vs. 2.38 ± 0.40, P < 0.05) while mRNA expression of RYR(2) was significantly higher (4.39 ± 4.68 vs. 1.49 ± 1.69, P < 0.05) in the aged dogs than in the adult dogs. mRNA expression of SECRA(2) and Calpain-I was similar between the two groups. Similarly, the protein expression level of Ca(V1.2) was significantly lower (0.13 ± 0.10 vs. 0.29 ± 0.12, P < 0.05) while the protein expression level of RYR(2) was significantly higher (0.18 ± 0.21 vs. 0.08 ± 0.36, P < 0.05) in the aged dogs than in the adult dogs. Again, protein expression of SECRA(2), PLN(1) and Calpain-I was similar between the two groups. CONCLUSION: These data suggest that aging could induce mRNA and protein expression changes of Ca(V1.2) and RYR(2) of LVDCC which might serve as the molecular basis of I(Ca-L) remodeling in aged dogs and might be linked to the increased likelihood of developing atrial fibrillation (AF) in aged dogs.