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In wireless sensor networks (WSNs), energy preservation through clustering and routing protocols has been verified as a significant effective method to extend the network lifetime. However, hot spot problem, excessive message overhead used for cluster formation, and frequent cluster maintenance are still the main challenges in clustering and routing protocols. The objective of this paper is to overcome these problems to enhance the network lifetime by proposing a new protocol combined Harris Harks Optimization Clustering with Fuzzy Routing named as HHOCFR. In HHOCFR, an improved Harris harks optimization (HHO) algorithm is utilized to select the best cluster heads (CHs) and form optimal clusters simultaneously by a novel encoding mechanism. Moreover, good point set based population initialization and neighborhood centroid opposition based learning mechanism are used to accelerate convergence and avoid being trapped into local optima. Thus, no extra message is needed for cluster formation. In addition, a fuzzy logic system (FLS) considers residual energy, energy consumption deviation of cluster, and distance to crossover point as descriptors to make decision on relay CH determination for each CH, resulting in energy balance among CHs so as to mitigate the hot spot problem. Thereafter, the CHs monitor the energy of the clusters to determine whether the rotation of CHs or re- clustering is started to maintain the clusters, which further decreases energy consumption of the network. According to the results, the average network lifetime of HHOCFR has increased by 34.20%, 28.11%, 23.65% and 17.43%, compared to IBRE-LEACH, DAPFL, IHHO-F and HHO-UCRA. For network throughput, HHOCFR is 12.7%, 13.51%, 20.95%, 10.87% higher than IBRE-LEACH, DAPFL, IHHO-F and HHO-UCRA. In addition, he energy consumption of HHOCFR is lower than IBRE-LEACH, DAPFL, IHHO-F and HHO-UCRA by 42.73%, 23.74%, 25.58%, 23.23%, respectively.

This study utilized particle image velocimetry (PIV) to analyze the kinematic and hydrodynamic characteristics of juvenile goldfish across three swimming modes: forward swimming, burst and coast, and turning. The results demonstrated that C-shaped turning exhibited the highest speed, enabling rapid and agile maneuvers for predator evasion. Meanwhile, forward swimming was optimal for sustained locomotion, and burst-and-coast swimming was suited for predatory behaviors. A vorticity analysis revealed that vorticity around the tail fin was the primary source of propulsive force, corroborating the correlation between vorticity magnitude and propulsion found in previous research. The findings emphasize the crucial role of the tail fin in swimming efficiency and performance. Future research should integrate ethology, biomechanics, and physiology to deepen the understanding of fish locomotion, potentially informing the design of efficient biomimetic underwater robots and contributing to fish conservation efforts.

Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) and Alzheimer's disease neuropathologic change (ADNC) are each associated with substantial cognitive impairment in aging populations. However, the prevalence of LATE-NC across the full range of ADNC remains uncertain. To address this knowledge gap, neuropathologic, genetic, and clinical data were compiled from 13 high-quality community- and population-based longitudinal studies. Participants were recruited from United States (8 cohorts, including one focusing on Japanese-American men), United Kingdom (2 cohorts), Brazil, Austria, and Finland. The total number of participants included was 6196, and the average age of death was 88.1 years. Not all data were available on each individual and there were differences between the cohorts in study designs and the amount of missing data. Among those with known cognitive status before death (n = 5665), 43.0% were cognitively normal, 14.9% had MCI, and 42.4% had dementia-broadly consistent with epidemiologic data in this age group. Approximately 99% of participants (n = 6125) had available CERAD neuritic amyloid plaque score data. In this subsample, 39.4% had autopsy-confirmed LATE-NC of any stage. Among brains with "frequent" neuritic amyloid plaques, 54.9% had comorbid LATE-NC, whereas in brains with no detected neuritic amyloid plaques, 27.0% had LATE-NC. Data on LATE-NC stages were available for 3803 participants, of which 25% had LATE-NC stage > 1 (associated with cognitive impairment). In the subset of individuals with Thal Aβ phase = 0 (lacking detectable Aβ plaques), the brains with LATE-NC had relatively more severe primary age-related tauopathy (PART). A total of 3267 participants had available clinical data relevant to frontotemporal dementia (FTD), and none were given the clinical diagnosis of definite FTD nor the pathological diagnosis of frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP). In the 10 cohorts with detailed neurocognitive assessments proximal to death, cognition tended to be worse with LATE-NC across the full spectrum of ADNC severity. This study provided a credible estimate of the current prevalence of LATE-NC in advanced age. LATE-NC was seen in almost 40% of participants and often, but not always, coexisted with Alzheimer's disease neuropathology.

An amendment to this paper has been published and can be accessed via the original article.

Objective: This study aimed to investigate the quality changes during the fermentation of sauerkraut without salt and inoculated with lactic acid bacteria and during low-temperature storage. Methods: The basic physicochemical indexes and quality changes of sauerkraut during fermentation were analyzed. Results: The unsalted sauerkraut reached maturity at 5 d of fermentation and the pH, nitrite content, reducing sugar content and vitamin C content decreased significantly (P

BackgroundMolecular tweezers (MTs) are broad-spectrum inhibitors of abnormal protein aggregation. A lead MT, called CLR01, has been demonstrated to inhibit the aggregation and toxicity of multiple amyloidogenic proteins in vitro and in vivo. Previously, we evaluated the effect of CLR01 in the 3 × Tg mouse model of Alzheimer's disease, which overexpresses mutant human presenilin 1, amyloid β-protein precursor, and tau and found that subcutaneous administration of the compound for 1 month led to a robust reduction of amyloid plaques, neurofibrillary tangles, and microgliosis. CLR01 also has been demonstrated to inhibit tau aggregation in vitro and tau seeding in cell culture, yet because in Alzheimer's disease (AD) and in the 3 × Tg model, tau hyperphosphorylation and aggregation are thought to be downstream of Aβ insults, the study in this model left open the question whether CLR01 affected tau in vivo directly or indirectly.MethodsTo determine if CLR01 could ameliorate tau pathology directly in vivo, we tested the compound similarly using the P301S-tau (line PS19) mouse model. Mice were administered 0.3 or 1.0 mg/kg per day CLR01 and tested for muscle strength and behavioral deficits, including anxiety- and disinhibition-like behavior. Their brains then were analyzed by immunohistochemical and biochemical assays for pathological forms of tau, neurodegeneration, and glial pathology.ResultsCLR01 treatment ameliorated muscle-strength deterioration, anxiety-, and disinhibition-like behavior. Improved phenotype was associated with decreased levels of pathologic tau forms, suggesting that CLR01 exerts a direct effect on tau in vivo. Limitations of the study included a relatively short treatment period of the mice at an age in which full pathology is not yet developed. In addition, high variability in this model lowered the statistical significance of the findings of some outcome measures.ConclusionsThe findings suggest that CLR01 is a particularly attractive candidate for the treatment of AD because it targets simultaneously the two major pathogenic proteins instigating and propagating the disease, amyloid β-protein (Aβ), and tau, respectively. In addition, our study suggests that CLR01 can be used for the treatment of other tauopathies in the absence of amyloid pathology.

Summary: Adenosquamous carcinoma (ASC) is frequently misdiagnosed or overlooked in clinical practice due to its dual histological components and potential transformation from either adenocarcinoma (ADC) or squamous cell carcinoma (SCC). Our study aimed to differentiate ASC from ADC and SCC by incorporating features of enhanced CTs and clinical characteristics to build radiomics and deep learning models. The classification models were trained in Xiangya Hospital and validated in two other independent hospitals. The areas under the receiver operating characteristic curves (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were used to estimate the performance. The optimal three-class classification model achieved a maximum AUC of 0.89 and accuracy of 0.81 in external validation sets, AUC of 0.99 and accuracy of 0.99 in the internal test set. These findings highlight the efficacy of our models in differentiating ASC, providing a non-invasive, timely, and accurate diagnostic approach before and during the treatment.

Abstract Biomass microbiota and chemical constituent are closely associated with final anaerobic fermentation performance. But the limiting factors affecting anaerobic fermentation quality and bacterial community have been rarely explored. This study aimed to elucidate the relative contribution of initial microbiota and chemical constituent of sweet sorghum on its final anaerobic fermentation quality. Sweet sorghum at two developmental stages (heading-stage, G1; hard-dough-stage, G2) was treated as follows: G1 microbiota + sterilized G1 (M1C1), G2 microbiota + sterilized G1 (M2C1), G1 microbiota + sterilized G2 (M1C2), and G2 microbiota + sterilized G2 (M2C2). The results showed that chemical constituent rather than microbiota changes remarkably influenced the production of lactic acid, propionic acid and ammonia-N, the relative abundance of Lactobacillus, Weissella, Lactococcus, Pediococcus, and Pantoea of sweet sorghum after anaerobic fermentation. The chemical constituent was the key limiting factor affecting the anaerobic fermentation quality of sweet sorghum. This study could provide a reference for clarifying the key limiting factors affecting anaerobic fermentation and making recommendations for production. Graphical Abstract

BackgroundRepeated failure of drug candidates targeting Alzheimer's disease (AD) in clinical trials likely stems from a lack of understanding of the molecular mechanisms underlying AD pathogenesis. Recent research has highlighted synergistic interactions between aggregated amyloid-β (Aβ) and tau proteins in AD, but the molecular details of how these interactions drive AD pathology remain elusive and speculative.MethodsHere, we test the hypothesis that Aβ potentiates intracellular tau aggregation, and show that oligomeric Aβ specifically exacerbates proteopathic seeding by tau. Using tau-biosensor cells, we show that treatment with sub-toxic concentrations of Aβ oligomers, but not monomers or fibrils, "primes" cells, making them more susceptible to tau seeding. The treatment with Aβ oligomers enhances intracellular tau aggregation in a dose-dependent manner when the cells are seeded with either recombinant or brain-derived tau fibrils, whereas little or no aggregation is observed in the absence of Aβ-oligomer priming.ResultsPriming by Aβ oligomers appears to be specific to tau, as α-synuclein seeding is unaffected by this treatment. Aβ oligomer-enhanced tau seeding also occurs in primary mouse neurons and human neuroblastoma cells. Using fluorescently labeled tau seeds, we find that treatment with Aβ oligomers significantly enhances the cellular uptake of tau seeds, whereas a known tau-uptake inhibitor blocks the effect of Aβ on tau uptake.ConclusionThe ability of Aβ to promote tau seeding suggests a specific and plausible mechanism by which extracellular Aβ initiates a deleterious cascade that is unique to AD. These data suggest that the Aβ-mediated potentiation of tau uptake into cells should also be taken into account when designing Aβ-targeted therapeutics.

BackgroundTo predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.MethodsThis study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.ResultsTo predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.ConclusionsThis study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

Self-assembly of the microtubule-associated protein tau into neurotoxic oligomers, fibrils, and paired helical filaments, and cell-to-cell spreading of these pathological tau species are critical processes underlying the pathogenesis of Alzheimer's disease and other tauopathies. Modulating the self-assembly process and inhibiting formation and spreading of such toxic species are promising strategies for therapy development. A challenge in investigating tau self-assembly in vitro is that, unlike most amyloidogenic proteins, tau does not aggregate in the absence of posttranslational modifications (PTM), aggregation inducers, or preformed seeds. The most common induction method is addition of polyanions, such as heparin; yet, this artificial system may not represent adequately tau self-assembly in vivo, which is driven by aberrant phosphorylation and other PTMs, potentially leading to in vitro data that do not reflect the behavior of tau and its interaction with modulators in vivo. To tackle these challenges, methods for in vitro phosphorylation of tau to produce aggregation-competent forms recently have been introduced ( Despres et al. ( 2017 ) Proc. Natl. Acad. Sci. U.S.A. , 114 , 9080 - 9085 ). However, the oligomerization, seeding, and interaction with assembly modulators of the different forms of tau have not been studied to date. To address these knowledge gaps, we compared here side-by-side the self-assembly and seeding activity of heparin-induced tau with two forms of in vitro phosphorylated tau and tested how the molecular tweezer CLR01, a negatively charged compound, affected these processes. Tau was phosphorylated by incubation either with activated extracellular signal-regulated kinase 2 or with a whole rat brain extract. Seeding activity was measured using a fluorescence-resonance energy transfer-based biosensor-cell method. We also used solution-state NMR to investigate the binding sites of CLR01 on tau and how they were impacted by phosphorylation. Our systematic structure-activity relationship study demonstrates that heparin-induced tau behaves differently from in vitro phosphorylated tau. The aggregation rates of the different forms are distinct as is the intracellular localization of the induced aggregates, which resemble brain-derived tau strains suggesting that heparin-induced tau and in vitro phosphorylated tau have different conformations, properties, and activities. CLR01 inhibits aggregation and seeding of both heparin-induced and in vitro phosphorylated tau dose-dependently, although heparin induction interferes with the interaction between CLR01 and tau.

Alzheimer's disease (AD) pathology is characterized by the aggregation of beta-amyloid (Aβ) and tau in the form of amyloid plaques and neurofibrillary tangles in the brain. It has been found that a synergistic relationship between these two proteins may contribute to their roles in disease progression. However, how Aβ and tau interact has not been fully characterized. Here, we analyze how tau seeding or aggregation is influenced by different Aβ self-assemblies (fibrils and oligomers). Our cellular assays utilizing tau biosensor cells show that transduction of Aβ oligomers into the cells greatly enhances seeded tau aggregation in a concentration-dependent manner. In contrast, transduced Aβ fibrils slightly reduce tau seeding while untransduced Aβ fibrils promote it. We also observe that the transduction of α-synuclein fibrils, another amyloid protein, has no effect on tau seeding. The enhancement of tau seeding by Aβ oligomers was confirmed using tau fibril seeds derived from both recombinant tau and PS19 mouse brain extracts containing human tau. Our findings highlight the importance of considering the specific form and cellular location of Aβ self-assembly when studying the relationship between Aβ and tau in future AD therapeutic development.

BackgroundA deep learning (DL) model based on representative biopsy tissues can predict the recurrence and overall survival of patients with glioma, leading to optimized personalized medicine. This research aimed to develop a DL model based on hematoxylin-eosin (HE) stained pathological images and verify its diagnostic accuracy.MethodsOur study retrospectively collected 162 patients with glioma and randomly divided them into a training set (n = 113) and a validation set (n = 49) to build a DL model. The HE-stained slide was segmented into a size of 180 × 180 pixels without overlapping. The patch-level features were extracted by the pre-trained ResNet50 to predict the recurrence and overall survival. Additionally, a light-strategy was introduced where low-size digital biopsy images with clinical information were inputted into the DL model to ensure minimum memory occupation.ResultsOur study extracted 512 histopathological features from the HE-stained slides of each glioma patient. We identified 36 and 18 features as significantly related to disease-free survival (DFS) and overall survival (OS), respectively, (P < 0.05) using the univariate Cox proportional-hazards model. Pathomics signature showed a C-index of 0.630 and 0.652 for DFS and OS prediction, respectively. The time-dependent receiver operating characteristic (ROC) curves, along with nomograms, were used to assess the diagnostic accuracy at a fixed time point. In the validation set (n = 49), the area under the curve (AUC) in the 1- and 2-year DFS was 0.955 and 0.904, respectively, and the 2-, 3-, and 5-year OS were 0.969, 0.955, and 0.960, respectively. We stratified the patients into low- and high-risk groups using the median hazard score (0.083 for DFS and−0.177 for OS) and showed significant differences between these groups (P < 0.001).ConclusionOur results demonstrated that the DL model based on the HE-stained slides showed the predictability of recurrence and survival in patients with glioma. The results can be used to assist oncologists in selecting the optimal treatment strategy in clinical practice.

Acquired radioresistance is a challenge for the cure of glioblastoma. Here, the authors show that radioresistant glioblastoma boosts mitochondrial fatty acid oxidation that fuels cell proliferation and induces immunosuppression via CD47 mediated anti-phagocytosis. Inhibition of FAO by etomoxir combined with anti-CD47 antibodies sensitizes glioblastoma to radiotherapy.

In the field of medical image fusion, traditional approaches often fail to differentiate between the unique characteristics of each raw image, leading to fused images with compromised texture and structural clarity. Addressing this, we introduce an advanced multi-branch fusion method characterized by contrast-enhanced features and interactive information exchange. This method integrates a multi-scale residual module and a gradient-dense module within a private branch to precisely extract and enrich texture details from individual raw images. In parallel, a common feature extraction branch, equipped with an information interaction module, processes paired raw images to synergistically capture complementary and shared functional information across modalities. Additionally, we implement a sophisticated attention mechanism tailored for both the private and public branches to enhance global feature extraction, thereby significantly improving the contrast and contour definition of the fused image. A novel correlation consistency loss function further refines the fusion process by optimizing the information sharing between modalities, promoting the correlation among basic cross-modal features while minimizing the correlation of high-frequency details across different modalities. Objective evaluations demonstrate substantial improvements in indices such as EN, MI, QMI, SSIM, AG, SF, and Q AB/F , with average increases of 23.67%, 12.35%, 4.22%, 20.81%, 8.96%, 6.38%, and 25.36%, respectively. These results underscore our method’s superiority in achieving enhanced texture detail and contrast in fused images compared to conventional algorithms, as validated by both subjective assessments and objective performance metrics. [ABSTRACT FROM AUTHOR]

Backgroud: Supernatants from various cytological samples, including body cavity effusion, sputum, bronchoalveolar lavage fluid (BALF), and needle aspiration, have been validated for detecting genetic alterations using cell‐free DNA (cfDNA) in patients with non‐small cell lung cancer (NSCLC). However, the sensitivity of fusion variations detection remains challenging. The protection of cell‐free RNA (cfRNA) is critical for resolving the issue. Methods: A protective solution (PS) was applied for preserving cfRNA in cytological supernatant (CS), and the quality of protected cfRNA was assessed by cycle threshold (CT) values from reverse transcription quantitative polymerase chain reaction (RT‐qPCR). Furthermore, we collected an additional set of malignant cytological and matched tumor samples from 84 NSCLC patients, cfDNA & cfRNA extraction and double detection for driver gene mutations was validated using the multi‐gene mutations detection by RT‐qPCR. Results: Under the optimal protection system, 91.0% (101/111) of cfRNA were protected effectively. Among the 84 NSCLC patient samples, seven cytological samples failed the tests. In comparison with tumor samples, the overall sensitivity and specificity of detecting driver genes of supernatant cfDNA and cfRNA were 93.8% (74/77) and 100% (77/77), respectively. Notably, when focusing exclusively on patients with fusion gene changes, both sensitivity and specificity reached 100% (11/11) for EML4‐ALK, ROS1, RET fusions, and MET ex14 skipping. Conclusion: These findings suggest that cfDNA & cfRNA extraction and double detection strategy recommended in this study improve the accuracy of driver genes mutations test, especially for RNA‐based assay. [ABSTRACT FROM AUTHOR]

Molecular tweezers (MTs) are broad-spectrum inhibitors of abnormal protein self-assembly, which act by binding selectively to lysine and arginine residues. Through this unique mechanism of action, MTs inhibit formation of toxic oligomers and aggregates. Their efficacy and safety have been demonstrated in vitro, in cell culture, and in animal models. Here, we discuss the application of MTs in diverse in vitro and in vivo systems, the experimental details, the scope of their use, and the limitations of the approach. We also consider methods for administration of MTs in animal models to measure efficacy, pharmacokinetic, and pharmacodynamic parameters in proteinopathies.

The emergence of immune checkpoint inhibitors (ICIs) has reshaped the landscape of advanced lung cancer treatment. The brain is the most common metastatic site for lung cancer. Whether conventional criteria can evaluate the intracranial response of ICIs remains unclear. Here, we report a well-documented case of intracranial necrosis confirmed by post-operative pathology after only one cycle of chemo-immunotherapy without any radiation therapy, which suggests that immunotherapy elicits strong anti-tumor responses for intracranial metastasis and promotes intracranial necrosis, resulting in a temporary increase in size of the target lesions. Still, the specific mechanisms and management strategies need to be further explored.