An integrated single-cell RNA-seq atlas of the mouse hypothalamic paraventricular nucleus links transcriptomic and functional types

The hypothalamic paraventricular nucleus (PVN) is a highly complex brain region that is crucial for homeostatic regulation through neuroendocrine signaling, outflow of the autonomic nervous system, and projections to other brain areas. In the past years, single-cell datasets of the hypothalamus have contributed immensely to the current understanding of the diverse hypothalamic cellular composition. While the PVN has been adequately classified functionally, its molecular classification is currently still insufficient. To address this, we created a detailed atlas of PVN transcriptomic cell types by integrating various PVN single-cell datasets into a recently published hypothalamus single-cell transcriptome atlas. Furthermore, we functionally profiled transcriptomic cell types, based on relevant literature, existing retrograde tracing data, and existing single-cell data of a PVN-projection target region. Finally, we validated our findings with immunofluorescent stainings. In our PVN atlas dataset, we identify the well-known different neuropeptide types, each composed of multiple novel subtypes. We identify Avp-Tac1, Avp-Th, Oxt-Foxp1, Crh-Nr3c1, and Trh-Nfib as the most important neuroendocrine subtypes based on markers described in literature. To characterize the preautonomic functional population, we integrated a single-cell retrograde tracing study of spinally projecting preautonomic neurons into our PVN atlas. We identify these (presympathetic) neurons to cocluster with the Adarb2+ clusters in our dataset. Further, we identify the expression of receptors for Crh, Oxt, Penk, Sst, and Trh in the dorsal motor nucleus of the vagus, a key region that the pre-parasympathetic PVN neurons project to. Finally, we identify Trh-Ucn3 and Brs3-Adarb2 as some centrally projecting populations. In conclusion, our study presents a detailed overview of the transcriptomic cell types of the murine PVN and provides a first attempt to resolve functionality for the identified populations.

Video-rate 3D imaging of living cells using Fourier view-channel-depth light field microscopy

Interrogation of subcellular biological dynamics occurring in a living cell often requires noninvasive imaging of the fragile cell with high spatiotemporal resolution across all three dimensions. It thereby poses big challenges to modern fluorescence microscopy implementations because the limited photon budget in a live-cell imaging task makes the achievable performance of conventional microscopy approaches compromise between their spatial resolution, volumetric imaging speed, and phototoxicity. Here, we incorporate a two-stage view-channel-depth (VCD) deep-learning reconstruction strategy with a Fourier light-field microscope based on diffractive optical element to realize fast 3D super-resolution reconstructions of intracellular dynamics from single diffraction-limited 2D light-filed measurements. This VCD-enabled Fourier light-filed imaging approach (F-VCD), achieves video-rate (50 volumes per second) 3D imaging of intracellular dynamics at a high spatiotemporal resolution of ~180 nm × 180 nm × 400 nm and strong noise-resistant capability, with which light field images with a signal-to-noise ratio (SNR) down to -1.62 dB could be well reconstructed. With this approach, we successfully demonstrate the 4D imaging of intracellular organelle dynamics, e.g., mitochondria fission and fusion, with ~5000 times of observation.

Softening of a flat phonon mode in the kagome ScV6Sn6

Geometrically frustrated kagome lattices are raising as novel platforms to engineer correlated topological electron flat bands that are prominent to electronic instabilities. Here, we demonstrate a phonon softening at the kz = π plane in ScV6Sn6. The low energy longitudinal phonon collapses at ~98 K and q = [Formula: see text] due to the electron-phonon interaction, without the emergence of long-range charge order which sets in at a different propagation vector qCDW = [Formula: see text]. Theoretical calculations corroborate the experimental finding to indicate that the leading instability is located at [Formula: see text] of a rather flat mode. We relate the phonon renormalization to the orbital-resolved susceptibility of the trigonal Sn atoms and explain the approximately flat phonon dispersion. Our data report the first example of the collapse of a kagome bosonic mode and promote the 166 compounds of kagomes as primary candidates to explore correlated flat phonon-topological flat electron physics.

A practical guide to deep-learning light-field microscopy for 3D imaging of biological dynamics

Here, we present a step-by-step protocol for the implementation of deep-learning-enhanced light-field microscopy enabling 3D imaging of instantaneous biological processes. We first provide the instructions to build a light-field microscope (LFM) capable of capturing optically encoded dynamic signals. Then, we detail the data processing and model training of a view-channel-depth (VCD) neural network, which enables instant 3D image reconstruction from a single 2D light-field snapshot. Finally, we describe VCD-LFM imaging of several model organisms and demonstrate image-based quantitative studies on neural activities and cardio-hemodynamics. For complete details on the use and execution of this protocol, please refer to Wang et al. (2021).1.

Adaptive super-resolution enabled on-chip contact microscopy

We demonstrate an adaptive super-resolution based contact imaging on a CMOS chip to achieve subcellular spatial resolution over a large field of view of ∼24 mm². By using regular LED illumination, we acquire the single lower-resolution image of the objects placed approximate to the sensor with unit magnification. For the raw contact-mode lens-free image, the pixel size of the sensor chip limits the spatial resolution. We develop a hybrid supervised-unsupervised strategy to train a super-resolution network, circumventing the missing of in-situ ground truth, effectively recovering a much higher resolution image of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area. We demonstrate the success of this approach by imaging the proliferation dynamics of cells directly cultured on the chip.

Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens

Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that through combining a microfluidic chip-enabled digital scanning light-sheet illumination strategy with deep-learning based image restoration, we can realize isotropic 3D imaging of a whole crawling Drosophila larva on an ordinary inverted microscope at a single-cell resolution and a high volumetric imaging rate up to 20 Hz. Enabled with high performances even unmet by current standard light-sheet fluorescence microscopes, we in toto record the neural activities during the forward and backward crawling of a 1st instar larva, and successfully correlate the calcium spiking of motor neurons with the locomotion patterns.

[Effects of protein disulfide isomerase on hyperglycemia and hypoxia/reoxygenation injury in H9c2 cardiomyocytes]

Objective: To explore the effect of protein disulfide isomerase (PDI) in diabetic ischemic heart disease. Methods: We established an in vitro model of high glucose and hypoxia/reoxygenation in H9c2 rat myocardial cells. Cultured cells were divided into four groups: Control, high glucose (HG), hypoxia/reoxygenation (H/R) and HG+H/R. Changes in PDI expression mediated by PDI adenovirus(Ad-PDI) infection and siRNA(PDI-siRNA) transfection in myocardial cells were observed by inverted fluorescence microscopy. We also measured lactate dehydrogenase(LDH) activity and malondialdehyde(MDA) and high molecular weight(HMW)-APN concentrations. PDI, APN, cleaved caspase-3, and glucose regulated protein 78 (Grp78) protein expression were detected. Results: PDI expression was significantly decreased in the HG, H/R and HG+H/R groups compared to the Control group; however, LDH activity[(179.7±10.4) U/L、(218.4±18.4) U/L、(328.2±5.3) U/L vs (91.0±11.0) U/L], MDA concentration[(7.0±0.4) μmol/L、(10.0±1.0) μmol/L、(11.7±1.0) μmol/L vs (4.2±1.8) μmol/L], cleaved caspase-3, and Grp78 expression were increased. Interestingly, APN and HMW-APN expression were decreased [(2.01±0.21) μg/L、(1.64±0.27) μg/L、(1.20±0.14) μg/L vs (2.62±0.12) μg/L, all P<0.05]. Over expression of PDI attenuated high glucose and hypoxia/reoxygenation induced apoptosis and oxidative stress in H9c2 cardiomyocytes(all P<0.05), and simultaneously increased APN and HMW-APN expression [(2.86±0.03) μg/L vs (3.03±0.10) μg/L、(2.06±0.05) μg/L vs (2.31±0.06) μg/L、(1.83±0.07) μg/L vs (1.96±0.11) μg/L、(1.20±0.06) μg/L vs (1.39±0.09) μg/L]. PDI-siRNA transfection increased LDH activity, MDA concentration, and cleaved caspase-3 and Grp78 expression, and decreased APN and HMW-APN expression [(0.75±0.09) μg/L vs (0.59±0.09) μg/L、(0.62±0.04) μg/L vs (0.53±0.05) μg/L、(0.55±0.14) μg/L vs (0.51±0.12) μg/L、(0.48±0.12) μg/L vs (0.35±0.08) μg/L] in response to different treatments in cultured H9c2 cardiomyocytes (all P<0.05). Conclusion: PDI may regulate the expression of APN and HMW-APN, and play an important role in the function of diabetic ischemia-reperfusion cardiomyocytes.

Construction of specific Smo lentivirus and expression of infected pancreatic cancer cells positive for CD24CD44 surface antibody

This study aimed to construct a vector lentivirus carrying the Smo gene and transfect pancreatic cancer cells positive for CD24CD44 surface antibody and detect the infectivity. A lentivirus carrying a specific Smo fragment was designed and synthesized, and its functionality was tested. An overexpression group, inhibitory group, and negative control group were used for subsequent experimental research and comparison. A virus was successfully designed and produced. The best viral load was the 1X106 TU virus, where the cell growth and fluorescence effect of culture wells with polybrene dilution were the best. These are the transfection conditions and transfection param-eters for subsequent experiments. This plasmid was detected with a flag antibody by Western blot. The result was that it had a large specific 250kD band, and the membrane protein was overexpressed successfully. The expression results of Smo in five groups of cells after virus transfection detected by RT-PCR: blank group were 1.0038±0.0344, CON238 negative group: 1.0276±0.2944d, CON077 negative group: 0.8793±0.0402; LV-SMO15570-2 overexpres-sion group: 2.7479±0.8308, and LV-SMO-RNAi37304-1 inhibition group: 0.2386±0.0481. There were differences among the overexpression group and inhibition group with the other three groups. Homogeneity of variance: Bartlett F = 4.3530, P = 0.0016 < 0.05, heterogeneous. K-W test: cc2 = 10.9905* P = 0.0267, and there was a statisti-cally significant difference. The designed virus achieved the goal requirements. An sRNA fragment was designed for the key gene Smo of the Hh signaling pathway, and a vector lentivirus carrying this fragment was successfully constructed. The expression of Smo was analyzed after transfecting SW1990CD24CD44 positive cells, suggesting that the function of the RNA fragment designed for the key gene Smo in this experiment was successful.

Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning

Light-field microscopy has emerged as a technique of choice for high-speed volumetric imaging of fast biological processes. However, artifacts, nonuniform resolution and a slow reconstruction speed have limited its full capabilities for in toto extraction of dynamic spatiotemporal patterns in samples. Here, we combined a view-channel-depth (VCD) neural network with light-field microscopy to mitigate these limitations, yielding artifact-free three-dimensional image sequences with uniform spatial resolution and high-video-rate reconstruction throughput. We imaged neuronal activities across moving Caenorhabditis elegans and blood flow in a beating zebrafish heart at single-cell resolution with volumetric imaging rates up to 200 Hz.

Progress in the study of markers related to glioma prognosis

OBJECTIVE

In the era of precision medicine, molecular and genetic biomarkers act as the key indicators for glioma patients' recurrence and prognosis.

MATERIALS AND METHODS

We summarize the biomarkers of glioma prognosis from molecular level, gene level and microRNA level.

RESULTS

In molecular biomarkers, cyclinD1 high expression/P16 low expression, MIF high expression and VEGF high expression were all related to glioma patients' poor prognosis; in genetic biomarkers, MGMT promoter methylation absence, IDH1 wild type, HIF-α high expression, Chromosome 1p/19q non-deletion and TERT promoter mutation were associated with poor prognosis for glioma; in microRNA biomarkers, miR-524-5p, miR-586, miR-433, miR-619, miR-548d-5p, miR-525-5p, miR-301a, miR-210, miR-10b-5p, miR-15b-5p and miRNA-182 high expression, miR-124, miR-128, miR-146b and miR-218 low expression were commonly seen in glioma poor prognosis patients.

CONCLUSIONS

With the continuous development of science and technology, the diagnosis of glioma will tend to the gene and molecular level. Finding specific markers is helpful for the early diagnosis and accurate prognosis of glioma, which provides the possibility for individualized treatment.

Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence

BACKGROUND

Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients' treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses.

METHODS

Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany.

RESULTS

Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells.

CONCLUSIONS

This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

[The role of time-series propagation map and activity path of confirmed cases in the analysis and determination of COVID-19 epidemic]

Objective: The time sequence transmission map and the cases travel track were used to explain the chain of transmission, describe the characteristics of transmission and analyze the mode of epidemic of novel coronavirus pneumonia, so as to provide evidence for the relevant government departments to carry out epidemic prevention and control. Methods: The time sequence transmission map and the cases travel track table were drawn, according to the time of incidence, age, sex, number of close contacts and their interrelations. Results: At the end of February 10, 2020, 63 COVID-19 cases were reported in the research area. Among them, 57 cases were confirmed (1 deaths) and 6 cases were asymptomatic, 57 cases were imported cases (90.48%), 36 cases were reported by cluster epidemic (57.14%) among friends and relatives. Cases have been spread to the fourth generation. Conclusion: The time sequence transmission map and the cases travel track showed that, in the research area, the epidemic situation of COVID-19 was mainly caused by imported case, and the clustering transmission was the major spread model. The time sequence transmission map and the cases travel track are worth popularizing in the prevention and control of major infectious diseases.

Dissecting charge relaxation pathways in CdSe/CdS nanocrystals using femtosecond two-dimensional electronic spectroscopy

Exciton relaxation dynamics of CdSe and quasi-type-II CdSe/CdS core/shell nanocrystals were examined using femtosecond two-dimensional electronic spectroscopy (2DES). The use of 2DES allowed for determination of structure-specific and state-resolved carrier dynamics for CdSe nanocrystals formed with five, or fewer, CdS passivation monolayers (ML). For CdSe and CdSe/CdS nanocrystals formed with one through three MLs of CdS, excitation using broad bandwidth femtosecond visible laser pulses generated electron-hole pairs among the |X₁〉 = 2.14 eV and |X₂〉 = 2.27 eV exciton states. For both excitations, the electron is promoted to the lowest energy excited (1S_e) conduction-band state and the hole is in the 1S_3/2 (X₁) or 2S_3/2 (X₂) valence-band state. Therefore, the relaxation dynamics of the hot hole were isolated by monitoring the-time-dependent amplitude of 2DES cross peaks. The time constant for hot hole relaxation within the CdSe valence band was 150 ± 45 fs. Upon passivation by CdS, this hole relaxation time constant increased to 170 ± 30 fs (CdSe/CdS-3ML). This small increase was attributed to the formation of a graded, or alloyed, interfacial region that precedes the growth of a uniform CdS capping layer. The small increase in hole relaxation time reflects the larger nanocrystal volume of the CdSe/CdS system with respect to the CdSe nanocrystal core. In contrast, the dynamics of larger core/shell nanocrystals (≥4ML CdS) exhibited a picosecond buildup in 2DES cross-peak amplitude. This time-dependent response was attributed to interfacial hole transfer from CdS to CdSe valence-band states. Importantly, the 2DES data distinguish CdSe exciton relaxation from interfacial carrier transfer dynamics. In combination, isolation of structurally well-defined nanocrystals and state-resolved 2DES can be used to examine directly the influence of nanoscale structural modifications on electronic carrier dynamics, which are critical for developing nanocluster-based photonic devices.

The association between family factors and child behaviour problems using dyadic data

BACKGROUND

Parental psychopathology and family issues are key influence factors to child behaviour problems. This study aimed to investigate the dyadic impact of maternal and paternal depression and perceived family functioning on child behaviour problems.

METHODS

Both maternal and paternal depression, perceived family functioning and reported child behaviour problems were collected, respectively. Because of the interdependent characteristic of dyadic data, structural equation modelling was used to examine the relationship among all variables and the mutual influence between mother and father.

RESULTS

Results showed that father-perceived family functioning mediated the relationship between parental depression and child behaviour problems, but mother-perceived family functioning did not show this mediation effect. Meanwhile, maternal and paternal depression influenced both of their own and their partner's perceived family functioning.

CONCLUSIONS

The findings indicated that paternal psychopathology and family functioning should not be overlooked in child behaviour development. In addition, this study underscored the importance to investigate the different impact of father and mother on child development within a dyadic unit.

Gli1 expression in pancreatic ductal adenocarcinoma and its clinical significance

The aim of this study was to explore the correlation between the expression levels of Gli1 and p53 in pancreatic ductal adenocarcinoma (PDAC) and its pathological significance. Immunohistochemistry (IHC) was employed to measure the expression level of Gli1 and p53 in 85 sets of paraffin-embedded PDAC and corresponding para-carcinoma tissue specimens. The relationship between these results and the respective patients' clinicopathologic parameters was analyzed. IHC staining revealed that the expression levels of Gli1 and p53 in cancer tissues were evidently higher than that of para-carcinoma tissues (P < 0.05); while Gli1 expression levels correlated with the corresponding TNM stage and tumor infiltration depth, p53 expression level correlated with the respective TNM stage (P < 0.05). Taken together, this study demonstrates increased expression of Gli1 and p53 in PDAC, and proves that Gli1 could be apotential biomarker for prognostic judgment.