Association between morphologic features of intracranial distal arteries and brain atrophy indexes in cerebral small vessel disease: a voxel-based morphometry study.

Background: Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions. Method: A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions. Results: Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (ß = -0.428, p = 0.007) and density (ß = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear. Conclusion: The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

Research on the Method of Counting Wheat Ears via Video Based on Improved YOLOv7 and DeepSort.

The number of wheat ears in a field is an important parameter for accurately estimating wheat yield. In a large field, however, it is hard to conduct an automated and accurate counting of wheat ears because of their density and mutual overlay. Unlike the majority of the studies conducted on deep learning-based methods that usually count wheat ears via a collection of static images, this paper proposes a counting method based directly on a UAV video multi-objective tracking method and better counting efficiency results. Firstly, we optimized the YOLOv7 model because the basis of the multi-target tracking algorithm is target detection. Simultaneously, the omni-dimensional dynamic convolution (ODConv) design was applied to the network structure to significantly improve the feature-extraction capability of the model, strengthen the interaction between dimensions, and improve the performance of the detection model. Furthermore, the global context network (GCNet) and coordinate attention (CA) mechanisms were adopted in the backbone network to implement the effective utilization of wheat features. Secondly, this study improved the DeepSort multi-objective tracking algorithm by replacing the DeepSort feature extractor with a modified ResNet network structure to achieve a better extraction of wheat-ear-feature information, and the constructed dataset was then trained for the re-identification of wheat ears. Finally, the improved DeepSort algorithm was used to calculate the number of different IDs that appear in the video, and an improved method based on YOLOv7 and DeepSort algorithms was then created to calculate the number of wheat ears in large fields. The results show that the mean average precision (mAP) of the improved YOLOv7 detection model is 2.5% higher than that of the original YOLOv7 model, reaching 96.2%. The multiple-object tracking accuracy (MOTA) of the improved YOLOv7-DeepSort model reached 75.4%. By verifying the number of wheat ears captured by the UAV method, it can be determined that the average value of an L1 loss is 4.2 and the accuracy rate is between 95 and 98%; thus, detection and tracking methods can be effectively performed, and the efficient counting of wheat ears can be achieved according to the ID value in the video.

Monitoring Wheat Lodging at Various Growth Stages.

Lodging is one of the primary factors that reduce wheat yield; therefore, rapid and accurate monitoring of wheat lodging helps to provide data support for crop loss and damage response and the subsequent settlement of agricultural insurance claims. In this study, we aimed to address two problems: (1) calculating the wheat lodging area. Through comparative experiments, the SegFormer-B1 model can achieve a better segmentation effect of wheat lodging plots with a higher prediction rate and a stronger generalization ability. This model has an accuracy of 96.56%, which realizes the accurate extraction of wheat lodging plots and the relatively precise calculation of the wheat lodging area. (2) Analyzing wheat lodging areas from various growth stages. The model established, based on the mixed-stage dataset, generally outperforms those set up based on the single-stage datasets in terms of the segmentation effect. The SegFormer-B1 model established based on the mixed-stage dataset, with its mIoU reaching 89.64%, was applicable to wheat lodging monitoring throughout the whole growth cycle of wheat.

Case report: Meningitis and intracranial aneurysm caused by mixed infection of oral microflora dominated by anaerobes.

Introduction: Meningitis caused by oral anaerobic bacteria is rare, especially when complicated with an infected intracranial aneurysm. This paper has described an extremely rare case of bacterial meningitis caused by a mixed infection of oral microflora dominated by anaerobes, which developed cerebral infarcts, brain abscess, intracranial aneurysm, and severe hydrocephalus during treatment. Case report: We describe a 65-year-old male patient who was presented with fever and headache as the initial symptoms and then developed left ophthalmoplegia, right hemiplegia, and disturbance of consciousness. Brain imaging showed that intracranial lesions were increased progressively, and cerebral infarcts, brain abscesses, intracranial aneurysm, and severe hydrocephalus were appeared gradually. Eventually, we diagnosed it as anaerobic meningitis by making deoxyribonucleic acid sequencing from the brain abscess pus. After using an anti-microbial regimen that can sufficiently cover anaerobes, the patient's condition was effectively controlled. Conclusion: Anaerobic meningitis can cause a series of intracranial complications. Among them, the intracranial aneurysm is extremely rare. When evidence shows that the infection originates from oral flora, physicians should consider the possibility of this type of encephalitis. An early diagnosis and timely treatment are crucial to improving the prognosis.

MiR-204-5p Alleviates Neuropathic Pain by Targeting BRD4 in a Rat Chronic Constrictive Injury Model.

Purpose: The pathogenesis of neuropathic pain is complex, and previous studies have found that microRNAs are important regulators of neuropathic pain and are associated with the progression of neuropathic pain. This study aims to explore the level and role of miR-204-5p in the chronic constrictive injury (CCI) model of rats. Patients and Methods: The CCI rat model was constructed to evaluate paw withdrawal threshold (PWT), paw withdrawal latency (PWL), the expressions of miR-204-5p, and the contents of inflammatory factors in the model. Overexpression of miR-204-5p in rat spinal cord was induced by intrathecal injection of miR-204-5p mimics. PWT and PWL were used to estimate mechanical and thermal pain thresholds. IL-6 and TNF-α were determined by ELISA. Luciferase reporter gene was conducted to verify the targeting relationship between miR-204-5p and BRD4. Results: miR-204-5p was abnormally down-regulated in the CCI group. The thresholds of mechanical and thermal pain stimulation in the CCI group were lower, and the levels of inflammatory factors were higher than those in the sham group. Overexpression of miR-204-5p alleviated PWT, PWL and inflammatory factors. Besides, the luciferase reporter gene showed that BRD4 was a target gene of miR-204-5p. Conclusion: These results suggested that miR-204-5p may alleviate neuropathic pain and inflammation through targeted regulation of BRD4 expression.

Deep multi-kernel auto-encoder network for clustering brain functional connectivity data.

In this study, we propose a deep-learning network model called the deep multi-kernel auto-encoder clustering network (DMACN) for clustering functional connectivity data for brain diseases. This model is an end-to-end clustering algorithm that can learn potentially advanced features and cluster disease categories. Unlike other auto-encoders, DMACN has an added self-expression layer and standard back-propagation is used to learn the features that are beneficial for clustering brain functional connectivity data. In the self-expression layer, the kernel matrix is constructed to extract effective features and a new loss function is proposed to constrain the clustering portion, which enables the training of a deep neural learning network that tends to cluster. To test the performance of the proposed algorithm, we applied the end-to-end deep unsupervised clustering algorithm to brain connectivity data. We then conducted experiments based on four public brain functional connectivity data sets and our own functional connectivity data set. The DMACN algorithm yielded good results in various evaluations compared with the existing clustering algorithm for brain functional connectivity data, the deep auto-encoder clustering algorithm, and several other relevant clustering algorithms. The deep-learning-based clustering algorithm has great potential for use in the unsupervised recognition of brain diseases.

A target screening method for detection of organic pollutants in fruits and vegetables by atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry combined with informatics platform.

This study employed an atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry (APGC-QTOF-MS) combined with UNIFI scientific platform to establish a scientific screening library for the screening of 104 organic contaminants in fruits and vegetables. The developed approach shortened the analysis time in comparison with the traditional gas chromatography mass spectrometer (GC-MS/MS). All compounds can be separated by using the three-dimensional (3D) acquisition mode supported by UNIFI platform. The percentage of organic contaminants detected with the tolerance ( ± 5 ppm mass accuracy and ± 0.2 min retention time) was in the range 71.4 ± 8.7%-93.3 ± 1.03% at the 10 µg kg-1 and 94.3 ± 1.2%-99.0 ± 3.4% at the 50 µg kg-1. The estimated limit of detection (LODs) of the 104 organic contaminants in different matrixes was between 0.02 and 6.00 µg kg-1. The scientific screening library and UNIFI informatics platform were successfully applied to monitor the target analytes in fruit and vegetable samples.

Quantum dot-based molecular imaging of cancer cell growth using a clone formation assay.

This aim of the present study was to investigate clonal growth behavior and analyze the proliferation characteristics of cancer cells. The MCF­7 human breast cancer cell line, SW480 human colon cancer cell line and SGC7901 human gastric cancer cell line were selected to investigate the morphology of cell clones. Quantum dot­based molecular targeted imaging techniques (which stained pan­cytokeratin in the cytoplasm green and Ki67 in the cell nucleus yellow or red) were used to investigate the clone formation rate, cell morphology, discrete tendency, and Ki67 expression and distribution in clones. From the cell clone formation assay, the MCF­7, SW480 and SGC7901 cells were observed to form clones on days 6, 8 and 12 of cell culture, respectively. These three types of cells had heterogeneous morphology, large nuclear:cytoplasmic ratios, and conspicuous pathological mitotic features. The cells at the clone periphery formed multiple pseudopodium. In certain clones, cancer cells at the borderline were separated from the central cell clusters or presented a discrete tendency. With quantum dot­based molecular targeted imaging techniques, cells with strong Ki67 expression were predominantly shown to be distributed at the clone periphery, or concentrated on one side of the clones. In conclusion, cancer cell clones showed asymmetric growth behavior, and Ki67 was widely expressed in clones of these three cell lines, with strong expression around the clones, or aggregated at one side. Cell clone formation assay based on quantum dots molecular imaging offered a novel method to study the proliferative features of cancer cells, thus providing a further insight into tumor biology.

Prognostic significance of tumor-associated macrophages density in gastric cancer: a systemic review and meta-analysis.

INTRODUCTION: Tumor-associated macrophages (TAM) play a dual role in the development of gastric cancer (GC). This study aims to analyze the prognostic value of TAM density in GC patients. EVIDENCE ACQUISITION: We conducted a meta-analysis of 11 studies (N.=1043) to investigate the correlation between TAM density and the overall survival (OS) or disease free survival (DFS) of GC patients. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by the STATA statistical software. EVIDENCE SYNTHESIS: The HR of OS of GC patients with high-density TAM is 1.56 (95% CI: 0.90~2.22, P<0.001) as compared with those with low-density TAM, and that of DFS is 1.10 (95% CI: 0.16~2.03, P=0.022), indicating that TAM density does not significantly predict the poor survival of GC. A subgroup analysis by ethnicity also revealed no significance effect between TAM density and a worse OS among both Asians and Caucasians (Asians: HR=1.47, 95% CI: 0.76~2.18, P<0.001; Caucasians: HR=2.23, 95% CI: 0.62~3.84, P=0.007, respectively). CONCLUSIONS: Our findings provide empirical evidence that TAM density is not an independent predictor for the survival of GC patients.

Morphological study and comprehensive cellular constituents of milky spots in the human omentum.

OBJECTIVE: To analyze morphological features of omental milky spots (MS). METHOD: Hematoxylin-eosin staining and immunohistochemistry technique were used to study the omental MS of gastric cancer (GC) patients and rectal cancer (RC) patients. We focused on morphological features of MS and conducted quantitative analysis on the cells number and cellular constituents. Differences in MS parameters between GC and RC were also analyzed. RESULTS: Various shapes of MS were mainly round, oval, irregular form in the adipose and perivascular annular. The median MS perimeter was 2752 (range 817~7753) computer-based pixels. The median value of immune cells in one MS was 141 (43~650), comprising T lymphocytes (46.1%), B lymphocytes (28.4%), macrophages (12.4%) and other immune cells (13.1%). Relatively high density of vessels in MS could be calculated by micro-vessel density (MVD) as 4 (0~13). The median value of mesothelial cells loosely arranged in the surface layer was 5 (0~51). There were no significant differences in MS perimeter, MVD, the number of mesothelial cells, total immune cells, T lymphocytes and macrophages between GC and RC (P>0.05), while the number of MS B lymphocytes in RC was significantly higher than that in GC (P<0.001). CONCLUSION: MS are primary immune tissues in the omentum and structural bases for development and progression of peritoneal dissemination of GC and RC. Analyzing the morphology and cellular constituents could help understanding the mechanism of peritoneal metastasis.

Anti-cancer effects of novel doxorubicin prodrug PDOX in MCF-7 breast cancer cells.

Ac-Phe-Lys-PABC-DOX (PDOX) is a smart doxorubicin (DOX) prodrug designed to decrease toxicities while maintaining the potent anticancer effects of DOX. This study was aimed at elucidating the effectiveness and toxicities of DOX and PDOX in patient-derived MCF-7 breast cancer cells in vitro. The MCF-7 cells were exposed to both PDOX and DOX, and cytotoxicities, cell cycle and P53/P21 signaling alterations were studied. Abundant cathepsin B was found in the MCF-7 cells, and treatment with PDOX and DOX triggered dose- and time-dependent cytotoxicity and resulted in a significant reduction in cell viability. The IC50 of PDOX and DOX was 3.91 and 0.94 µmol/L, respectively. Both PDOX and DOX caused an up-regulation of the P53/P21-related signal pathway, and PDOX significantly increased expression of P53 and caspase 3, and arrested the cell cycle at the G1/G2 phase. As compared with DOX, PDOX reduced toxicities, and it may have different action mechanisms on breast cancer cells.

Distribution of poly- and perfluoroalkyl substances in matched samples from pregnant women and carbon chain length related maternal transfer.

Although levels of poly- and perfluoroalkyl substances (PFASs) in human maternal and neonatal blood have been widely reported in the literature, relationship of maternal-fetal transmission of PFASs with carbon chain length is presently not well understood. In this study, 11 PFASs were analyzed in matched samples, including not only maternal blood (MB, n = 31) and cord blood (CB, n = 30), but also placenta (n = 29) and amniotic fluid (AF, n = 29). Except for perfluorohexanoic acid (PFHxA), the detection frequencies of PFASs were similar among placenta, MB, and CB (>80% for 8 PFASs, nondetectable for 2 PFASs). Though only perfluorooctanoic acid (PFOA) was frequently detected (>90%) in AF, with a median concentration of 0.043 ng/mL, other 5 PFASs were also detectable in AF samples with low concentrations (mean: 0.013-0.191 ng/mL). This suggests that in addition to blood-borne in utero exposure, the fetus is also exposed to low levels of PFASs through AF. Concentrations of PFOA in AF were positively correlated with those in MB (r = 0.738, p < 0.01) and CB (r = 0.683, p < 0.001), suggesting that AF concentration could reflect fetal PFOA exposure during pregnancy and can be used as a biomarker. To clarify the effects of carbon chain length on maternal transfer of PFASs, we calculated maternal transfer efficiencies of PFASs from MB to CB (TMB-CB). A U-shaped trend in TMB-CB of C7-C12 perfluoroalkyl carboxylic acids (PFCAs) with increasing carbon chain length was found in this study for the first time. The U-shaped TMB-CB of PFCAs with carbon chain length is an integrated result of opposite trend of the ratios between MB/placenta and placenta/CB based on carbon chain length. This is the first study to report the occurrence of PFASs in human placenta. The results reported here enable better understanding of the maternal-fetal transmission of PFASs.

Fluorescent sensing ochratoxin A with single fluorophore-labeled aptamer.

We explored a fluorescent strategy for sensing ochratoxin A (OTA) by using a single fluorophore-labeled aptamer for detection of OTA. This method relied on the change of the fluorescence intensity of the labeled dye induced by the specific binding of the fluorescent aptamer to OTA. Different fluorescein labeling sites of aptamers were screened, including the internal thymine bases, 3'-end, and 5'-end of the aptamer, and the effect of the labeling on the aptamer affinity was investigated. Some fluorophore-labeled aptamers showed a signal-on or signal-off response. With the fluorescent aptamer switch, simple, rapid, and selective sensing of OTA at nanomolar concentrations was achieved. OTA spiked in diluted red wine could be detected, showing the feasibility of the fluorescent aptamer for a complex matrix. This method shows potential for designing aptamer sensors for other targets.

Screening interaction between ochratoxin A and aptamers by fluorescence anisotropy approach.

By taking advantage of the intrinsic fluorescence of ochratoxin A (OTA), we present a fluorescence anisotropy approach for rapid analysis of the interactions between OTA and aptamers. The specific binding of OTA with a 36-mer aptamer can induce increased fluorescence anisotropy (FA) of OTA as the result of the freedom restriction of OTA and the increase of molecular volume, and the maximum FA change is about 0.160. This FA approach enables an easy way to investigate the effects of buffer compositions like metal ions on the affinity binding. FA analysis shows the interaction between OTA and aptamer is greatly enhanced by the simultaneous presence of Ca(2+) and Na(+), while the binding affinity of aptamer decreases more than 18-fold when only Ca(2+) exists, and the binding is completely lost when Ca(2+) is absent. Crucial region of the aptamer for binding can be mapped through FA analysis and aptamer mutation. The demonstrated FA approach maintains the advantages of FA in simplicity, rapidity, and robustness. This investigation will help the development of aptamer-based assays for OTA detection in optimizing the binding conditions, modification of aptamers, and rational design.

Perfluorinated compounds in human blood, water, edible freshwater fish, and seafood in China: daily intake and regional differences in human exposures.

Despite the growing public interest in perfluorinated compounds (PFCs), very few studies have reported the sources and pathways of human exposure to these compounds in China. In this study, concentrations of 10 PFCs were measured in human blood, water (tap water and surface water), freshwater fish, and seafood samples collected from China. On the basis of the data, we calculated daily intakes of PFCs, regional differences in human exposures, and potential risks associated with ingestion of PFCs from diet, drinking water, and indoor dust for the Chinese population. Perfluorooctane sulfonate (PFOS) was the most predominant PFC found with a mean concentration of 12.5 ng/mL in human blood from Tianjin and 0.92 ng/g wet wt in freshwater fish and seafood; perfluorooctanoic acid (PFOA) was the major PFC found in drinking water at a concentration range of 0.10 to 0.92 ng/L. The estimated daily intake of PFOS and PFOA via fish and seafood consumption (EDI(fish&seafood)) ranged from 0.10 to 2.51 and 0.13 to 0.38 ng/kg bw/day, respectively, for different age groups (i.e., toddlers, adolescents and children, and adults) from selected locations (i.e., Tianjin, Nanchang, Wuhan, and Shenyang). The EDI(fish&seafood) of PFCs decreased (p < 0.05) with age. The estimated daily intake of PFOS and PFOA via drinking water consumption (EDI(drinking water)) ranged from 0.006 to 0.014 and 0.010 to 0.159 ng/kg bw/day, respectively. Comparison of EDI(fish&seafood) and EDI(drinking water) values with those of the modeled total dietary intake (TDI) of PFCs by adults from Tianjin, Nanchang, Wuhan, and Shenyang showed that contributions of fish and seafood to TDI of PFOS varied depending on the location. Fish and seafood accounted for 7%, 24%, 80%, and 84% of PFOS intake in Nanchang, Shenyang, Wuhan, and Tianjin, respectively, suggesting regional differences in human exposure to PFOS. Drinking water was a minor source of PFOS (<1%) exposure in adults from all the study locations.