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This article proposes an improved YOLOv5s counting method to address the problems of long-term manual counting of positive cells in immunohistochemical images and low consistency. First, by introducing the Triplet attention module, the model focuses on the positive cell area, reducing background interference and improving the network's ability to extract positive cell features; then, a small target detection layer is added to better utilize the semantic information of the network to improve positive cells. recognition accuracy; then, the lightweight up-sampling operator CARAFE is used to improve the quality and accuracy of up-sampling; finally, the WIoU loss function is used to replace the original GIoU of YOLOv5 to enhance model detection performance. Experimental results show that the improved model has an average accuracy of 88.4%, which is 3.1% higher than the original YOLOv5 network model. It can count positive cells quickly and accurately, reducing the workload of doctors.

The difficulty in pathological image diagnosis of gastric cancer lies in the accurate segmentation of cancerous tissue in the picture. To increase gastric cancer pathological images segmentation accuracy, we optimized the basic UNet model and proposed the DCU-Net model. First, add a direct channel module to each layer of the encoding part to obtain more detailed information. In addition, considering that the image may cause a loss of information during the transmission process, a CA module is added before the up-sampling and down-sampling of each layer so that the model can obtain more channel information. After conducting segmentation experiments on our own gastric cancer data set and comparing it with several current classic segmentation models. The experiment proved that the segmentation accuracy using this article's model can be enhanced on our own gastric cancer image segmentation data set, achieving an accuracy of 91.30% and an IoU of 79.88%.

Efficient and stable hole transport layer (HTL) is an important component of organic photovoltaics (OPV). Herein, a novel self‐assembled monolayer material of 4PADCB (short for (4‐(7H‐dibenzo[c,g]carbazol‐7‐yl)butyl)phosphonic acid) as HTL for non‐fullerene (NF) OPV is reported. Compared to the widely used PEDOT:PSS HTL, the usage of 4PADCB not only enhances photon incident and charge generation but also effectively improves the morphology of the upper active layer, promotes molecular packing, and balances the carrier transport within active layer. As a result, the single‐junction binary D18:L8BO OPV, employing 4PADCB as HTL, achieves a high‐power conversion efficiency (PCE) of 19.02% with excellent storage stability. Furthermore, a 19.3 cm2 OPV module comprising seven sub‐cells demonstrates a maximum PCE of 15.44%, which is the highest value of reported efficiency for large‐area binary OPV modules. Meanwhile, the module is the first demonstration of an OPV module based on self‐assembled monolayer material. This work underscores the substantial potential for the application of 4PADCB in efficient NF OPV devices and high‐throughput large‐area modules. [ABSTRACT FROM AUTHOR]

Miniaturized spectrometers that are absent of bulky dispersive optical elements have received more and more attention. However, most of these advancements have been demonstrated in the visible spectrum. Among the various near‐infrared (NIR) absorbers, organic donor–acceptor blends exhibit a distinctive red‐shifted intermolecular charge‐transfer (CT) state absorption, allowing for the detection of NIR photons below the distinct molecular band edge. Nevertheless, the sub‐bandgap absorption cross‐section has been rather limited. In this study, this challenge is addressed by integrating a metal–dielectric (M–D) microcavity into a prototype (PM6:Y6) model system, with a band‐edge positioned at 869 nm. As a result, an amplified narrowband detection, demonstrating an external quantum efficiency of ≈26% at 905 nm is achieved. Furthermore, the manipulation of the cavity lengths enables easy fine‐tuning of the narrowband spectral response within the 850–960 nm range. Leveraging a spectrum reconstruction algorithm, a spectral detector with 10 nm resolution under a zero bias, validating the potential of utilizing sub‐bandgap CT state absorption for efficient narrowband detectors and micro‐spectrometers is obtained. [ABSTRACT FROM AUTHOR]

Background: Plasma-based biomarkers would be potential biomarkers for early diagnosis of Alzheimer's disease (AD) because they are more available and cost-effective than cerebrospinal fluid (CSF) or neuroimaging. Therefore, we aimed to evaluate whether phosphorylated tau181 (p-tau181) in plasma could be an accurate AD predictor. Methods: Participants from the ADNI database included 185 cognitively unimpaired subjects with negative Aβ (CU–), 66 subjects with pre-clinical AD (CU with positive Aβ), 164 subjects with mild cognitive impairment with negative Aβ (MCI–), 254 subjects with prodromal AD (MCI with positive Aβ), and 98 subjects with dementia. Multiple linear regression models, linear mixed-effects models, and local regression were used to explore cross-sectional and longitudinal associations of plasma p-tau181 with cognition, neuroimaging, or CSF biomarkers adjusted for age, sex, education, and APOE genotype. Besides, Kaplan–Meier and adjusted Cox-regression model were performed to predict the risk of progression to dementia. Receiver operating characteristic analyses were performed to evaluate the predictive value of p-tau181. Results: Plasma p-tau181 level was highest in AD dementia, followed by prodromal AD and pre-clinical AD. In pre-clinical AD, plasma p-tau181 was negatively associated with hippocampal volume (β = −0.031, p -value = 0.017). In prodromal AD, plasma p-tau181 was associated with decreased global cognition, executive function, memory, language, and visuospatial functioning (β range −0.119 to −0.273, p -value < 0.05) and correlated with hippocampal volume (β = −0.028, p -value < 0.005) and white matter hyperintensity volume (WMH) volume (β = 0.02, p -value = 0.01). In AD dementia, increased plasma p-tau181 was associated with worse memory. In the whole group, baseline plasma p-tau181 was significantly associated with longitudinal increases in multiple neuropsychological test z -scores and correlated with AD-related CSF biomarkers and hippocampal volume (p -value < 0.05). Meanwhile, CU or MCI with high plasma p-tau181 carried a higher risk of progression to dementia. The area under the curve (AUC) of the adjusted model (age, sex, education, APOE genotype, and plasma p-tau181) was 0.78; that of additionally included CSF biomarkers was 0.84. Conclusions: Plasma p-tau181 level is related to multiple AD-associated cognitive domains and AD-related CSF biomarkers at the clinical stages of AD. Moreover, plasma p-tau181 level is related to the change rates of cognitive decline and hippocampal atrophy. Thus, this study confirms the utility of plasma p-tau181 as a non-invasive biomarker for early detection and prediction of AD. [ABSTRACT FROM AUTHOR]

Background: To evaluate the brain response to energy intake using cerebral blood flow(CBF) in Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy controls (HC) and its relationship with cognition. Method: A self‐comparison design was used to test the effects of energy intake on brain activity in participants with AD (n = 30), MCI participants (n = 32), and HC (n = 30) and its relationship with cognitive function. Brain perfusion was measured using arterial spin labeling (ASL) functional brain imaging. Participants arrived at the site in the morning and underwent the ASL‐MRI with at least 10 hours fasting overnight. Then the second ASL‐MRI at 30 minutes after eating a standard breakfast was performed. Energy response ΔCBF was computed by subtracting the fasting CBF from the postprandial CBF obtained from ASL‐MRI. Whole brain grey matter voxel‐wise paired T test and linear regression analyses were used for statistical analysis. Result: AD and MCI group had different energy response ΔCBF pattern with HC group. In AD group, energy intake induced a significantly decreased CBF in temporal lobe including lateral inferior and superior temporal gyrus, right superior temporal gyrus, parietal lobe including bilateral superior and inferior parietal lobe, postcentral gyrus and precuneus, most of occipital lobe and frontal lobe including right rolandic operculum, right precentral gyrus and left middle frontal gyrus. (q < 0.05, false discovery rate corrected). MCI had similar energy intake response pattern with AD. HC group had no significantly changed CBF response to energy intake. Energy response ΔCBF in the vicinity of the superior temporal gyrus showed significant negative correlation with Minimum Mental State Examination (MMSE) in all AD, MCI and HC groups. Conclusion: The different energy response ΔCBF pattern may help to characterize the energy disorder in AD and may indicate the different brain energy rescue effect in the three groups. Energy response ΔCBF in the superior temporal gyrus is an indicator of cognitive function in AD. [ABSTRACT FROM AUTHOR]

Background: The Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score, a validated tool estimating dementia risk, has been suggested to be associated with accelerated brain atrophy but the imaging biomarkers and AD pathologies remains to be elucidated. We aimed to explore the relationships of CAIDE score with cognition and AD‐related brain changes, including beta‐amyloid (Aβ) deposition and glucose metabolism and the mediation effect of the WMH on these associations. Method: A sample of 1,285 participants underwent CAIDE dementia risk assessment, of these, 958 individuals had a CAIDE score of less than or equal to 8. Memory and executive function were used to measure cognitive performance. We analyzed data using linear mixed‐effects and mediation. Result: CAIDE score was significantly associated with WMH volume, and also had significant association with Aβ deposition, AD‐metabolism, and memory and executive function. WMH volume mediated 6.04%, 12.87%, 6.93% and 7.92% of the total association of CAIDE score with memory, executive function, FDG‐PET and AV45‐PET, respectively. Conclusion: Memory, executive function, AD‐metabolism and Aβ deposition are strongly associated with dementia risk. Besides, the associations could be mediated by WMH volume and whether this represents a causal relationship remains to be determined. [ABSTRACT FROM AUTHOR]