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Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence assistive diagnostic solution, AIATBS, to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria. We train AIATBS with >81,000 retrospective samples. It integrates YOLOv3 for target detection, Xception and Patch-based models to boost target classification, and U-net for nucleus segmentation. We integrate XGBoost and a logical decision tree with these models to optimize the parameters given by the learning process, and we develop a complete cervical liquid-based cytology smear TBS diagnostic system which also includes a quality control solution. We validate the optimized system with >34,000 multicenter prospective samples and achieve better sensitivity compared to senior cytologists, yet retain high specificity while achieving a speed of <180s/slide. Our system is adaptive to sample preparation using different standards, staining protocols and scanners. Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study.

Macrophages acquire distinct phenotypes during tissue stress and inflammatory responses, but the mechanisms that regulate the macrophage polarization are poorly defined. Here we show that tuberous sclerosis complex 1 (TSC1) is a critical regulator of M1 and M2 phenotypes of macrophages. Mice with myeloid-specific deletion of TSC1 exhibit enhanced M1 response and spontaneously develop M1-related inflammatory disorders. However, TSC1-deficient mice are highly resistant to M2-polarized allergic asthma. Inhibition of the mammalian target of rapamycin (mTOR) fails to reverse the hypersensitive M1 response of TSC1-deficient macrophages, but efficiently rescues the defective M2 polarization. Deletion of mTOR also fails to reverse the enhanced inflammatory response of TSC1-deficient macrophages. Molecular studies indicate that TSC1 inhibits M1 polarization by suppressing the Ras GTPase–Raf1–MEK–ERK pathway in mTOR-independent manner, whereas TSC1 promotes M2 properties by mTOR-dependent CCAAT/enhancer-binding protein-β pathways. Overall, these findings define a key role for TSC1 in orchestrating macrophage polarization via mTOR-dependent and independent pathways. Macrophages can be polarized to inflammatory M1 and anti-inflammatory M2 phenotypes, depending on the cytokine milieu. Here, Zhu et al. demonstrate that tuberous sclerosis complex 1 (TSC1) inhibits M1 and promotes M2 polarization of macrophages to prevent inflammatory disorders.

Detecting small molecules is pivotal across fields like clinical diagnostics, environmental monitoring, and food safety. The CRISPR-Cas12a system, known for its simplicity and sensitivity, offers a promising basis for small molecule detection. However, current CRISPR-based detection methods face challenges, including complex design requirements, high background noise, and limited adaptability to different targets. In our study, we introduce the SBS-Cas system, leveraging a split crRNA mode to induce spatial hindrance on the scaffold strand through molecular binding. This approach prevents the assembly with Cas12a, effectively masking its trans-cleavage activity. By introducing small molecules that competitively bind to the macromolecule, we eliminate this spatial hindrance, activating Cas12a. Our results demonstrate high sensitivity, versatility, and adaptability in small molecule detection across multiple reactions, with successful intracellular imaging and responsive fluctuations in complex environments underscoring the system’s robustness. This innovative CRISPR-Cas12a-based approach establishes a low-background, highly sensitive platform for small molecule detection. SBS-Cas promises not only to enhance tools for clinical, environmental, and food safety applications but also to advance CRISPR research, providing insights and expanding possibilities in molecular detection science. Detecting small molecules is pivotal across many fields. Here, authors leverage a split crRNA mode to construct spatially blocked split CRISPR-Cas12a system. This approach establishes a low-background, highly sensitive platform for small molecule detection.

Programmed cell death (PCD) plays a crucial role in the development and homeostasis maintenance of multicellular organisms. Apoptosis is a form of PCD that prevents pathological development by eliminating damaged or useless cells. Despite the complexity of fungal apoptosis mechanisms being similar to those of plants and metazoans, fungal apoptosis lacks the core regulatory elements of animal apoptosis. Apoptosis-like PCD in fungi can be triggered by a variety of internal and external factors, participating in biological processes such as growth, development, and stress response. Although the core regulatory elements are not fully understood, apoptosis-inducing factor and metacaspase have been found to be involved. This article summarizes various proteins closely related to fungal apoptosis, such as apoptosis-inducing factor, metacaspase, and inhibitors of apoptosis proteins, as well as their structures and functions. This research provides new strategies and ideas for the development of natural drugs targeting fungal apoptosis and the control of fungal diseases.

Recent research has demonstrated a relationship between fruit and vegetable intake and gastrointestinal cancers, but the causality of these associations remains uncertain. This investigation sought to elucidate whether there is a potential causal relationship between the intake of fruits and vegetables and the risk of gastrointestinal cancers. Employing two-sample Mendelian randomization (MR), this research explored the causative influence of consuming fruits (fresh and dried) and vegetables (salads/raw and cooked) on the susceptibility to gastrointestinal cancers. The UK Medical Research Council-Integrative Epidemiology Unit (MRC-IEU) provided the summary statistics for these exposure variables, while the summary statistics for outcome data came from four other data sources. Univariable and multivariable MR were performed using inverse variance-weighted (IVW), MR-Egger, weighted media (WM), and Lasso model methods. Besides, multiple methods were employed for sensitivity analyses to guarantee the robustness of the findings, including MR-Egger intercept, Cochran’s Q test, and MR-PRESSO. Furthermore, the Phenoscanner V2 database was employed to identify possible confounders. The main analysis of univariable MR found that dried fruit consumption provided protection against pancreatic and oral cavity/pharyngeal cancers. However, this correlation becomes non-significant when potential confounders such as smoking, drinking, and body mass index (BMI) are accounted for. Furthermore, neither univariate nor multivariate MR analyses revealed enough data to prove a causal relationship between the intake of fresh fruit, vegetables (including salad/raw and cooked), and gastrointestinal cancers. There is insufficient evidence for a causal association between the consumption of fruits and vegetables and the occurrence of gastrointestinal cancers. Further empirical research is needed to corroborate these dietary factors’ role in the etiology of gastrointestinal cancers.

The aim of this study was to evaluate the effect of Lactobacillus delbrueckii subsp. lactis (L.del) on vaginal microbiota (VM) dysbiosis and vaginal radiation injury in gynecologic cancer patients. The inhibitory effects of L.del on cervical cancer cells were also studied in vitro. Gynecologic cancer patients receiving radiotherapy were randomized into control and L.del intervention groups. The control group received radiotherapy, while the intervention group received radiotherapy and L.del intervention (1 capsule/day placed into the deep vagina from the first day of radiotherapy until the end of treatment). Vaginal swab samples were collected on the first day pre-treatment and the last day post-treatment. DNA from 54 patients was extracted and assessed by the 16S rRNA sequencing method. Radiotherapy resulted in vaginal microbiome dysbiosis characterized by increased phylogenetic diversity and increased abundance of Brevundimonas , Streptococcus and Prevotella , but a decreased abundance of Lactobacillus . Level 2 vaginal radiation injury was positively associated with the abundance of Brevundimonas and gram-negative non-fermenting bacteria. Administration of L.del attenuated the reduction of Lactobacillus while also inhibiting the abundance of Streptococcus and Prevotella , thereby ameliorating radiotherapy-related vaginal microbiota dysbiosis. CLD inhibited the in vitro proliferation of SiHa cells by altering the expression of BCL2, HPV16-E6, HPV16-E7, IL6, MAP7, BAX, Caspase-3, Caspase-9 and LTF. In conclusion, L. del application can alleviate radiation-induced vaginal dysbiosis and restore Lactobacillus dominance of the vaginal microbiome. Moreover, CLD was found to inhibit cell growth and promote the apoptosis of SiHa cells in vitro. The registration number for this clinical trial is ChiCTR1900021784.

This study designs a spectrum data collection device and system based on the Internet of Things technology, aiming to solve the tedious process of chlorophyll collection and provide a more convenient and accurate method for predicting chlorophyll content. The device has the advantages of integrated design, portability, ease of operation, low power consumption, low cost, and low maintenance requirements, making it suitable for outdoor spectrum data collection and analysis in fields such as agriculture, environment, and geology. The core processor of the device uses the ESP8266-12F microcontroller to collect spectrum data by communicating with the spectrum sensor. The spectrum sensor used is the AS7341 model, but its limited number of spectral acquisition channels and low resolution may limit the exploration and analysis of spectral data. To verify the performance of the device and system, this experiment collected spectral data of Hami melon leaf samples and combined it with a chlorophyll meter for related measurements and analysis. In the experiment, twelve regression algorithms were tested, including linear regression, decision tree, and support vector regression. The results showed that in the original spectral data, the ETR method had the best prediction effect at a wavelength of 515 nm. In the training set, RMSEc was 0.3429, and Rc2 was 0.9905. In the prediction set, RMSEp was 1.5670, and Rp2 was 0.8035. In addition, eight preprocessing methods were used to denoise the original data, but the improvement in prediction accuracy was not significant. To further improve the accuracy of data analysis, principal component analysis and isolation forest algorithm were used to detect and remove outliers in the spectral data. After removing the outliers, the RFR model performed best in predicting all wavelength combinations of denoised spectral data using PBOR. In the training set, RMSEc was 0.8721, and Rc2 was 0.9429. In the prediction set, RMSEp was 1.1810, and Rp2 was 0.8683.

The therapeutic efficacy of programmed cell death protein 1/programmed cell death-ligand 1 (PD-1/PD-L1) blockade immunotherapy is extremely dampened by complex immunosuppressive mechanisms including regulatory T cells (Treg), M2 macrophages (M2), and prostaglandin E2 (PGE2). The pivotal roles of PGE2 have been recognized by directly inactivating CD8+ T cells and indirectly inducing Treg and M2. Therefore, PGE2 abolishment through inactivating cyclooxygenase-2 (COX-2) could be robust to sensitize tumour toward anti-PD-1/PD-L1 immunotherapy, which has gone into clinical trials. However, exploring this promising strategy in nanomedicine to enhance immunotherapy remains unrevealed. The key challenge to synergistically combine COX-2 inhibition and anti-PD-1/PD-L1 lies in the different pharmacokinetic profiles and the spatial obstacles since PD-1/PD-L1 interaction occurs extracellularly and COX-2 locates intracellularly. Thus, the programmed release nanoparticles (termed as Cele-BMS-NPs) are rationally designed, which are composed of pH-sensitive human serum albumin derivative, BMS-202 compound as PD-1/PD-L1 inhibitor, glutathione (GSH)-activatable prodrug of celecoxib (COX-2 inhibitor). The in vitro experiments demonstrate that this smart Cele-BMS-NPs could extracellularly release BMS-202 under the acidic tumour microenvironment, and the intracellularly release of celecoxib in response to the elevated GSH concentration inside tumour cells. After systemic administration, the intratumoral infiltration of CD8+ T cells is significantly enhanced and meanwhile immunosuppressive M2, Treg, and PGE2 are reduced, thereby eliciting the anti-tumour immune responses toward low immunogenic tumours and postsurgical tumour recurrences.

DNA molecules can be used to build “neural networks” that function like the brain, enabling them to perform complex computational tasks. However, a fundamental limitation of existing DNA networks is that their most basic computing units cannot perform true continuous and precise analog calculations, which restricts their ability to process complex information effectively. To address this, here we develop a DNA computing unit called CALCUL. This system successfully achieves fully analog computation, where all inputs, weighting parameters, and outputs are continuous and precise values. It performs the core operations of a neural network rapidly with high accuracy and is reusable. By integrating magnetic bead technology, we also enable modular operations and the construction of multilayer networks. Ultimately, we use this technology to construct a deep DNA neural network that correctly identifies complex color images with 100% accuracy. These developments provide a robust foundation for building more powerful and precise molecular computers. Achieving truly continuous and precise analog calculations using DNA neural networks is challenging. Here, the authors develop a fully analog DNA neural network system called CALCUL, that performs highly accurate weighted-sum operations and can be recycled.

Omega-3 polyunsaturated fatty acids (PUFAs) play beneficial roles in metabolism and health. Little is known about the effects of different doses of omega-3 PUFAs on gut microbiota.BACKGROUNDOmega-3 polyunsaturated fatty acids (PUFAs) play beneficial roles in metabolism and health. Little is known about the effects of different doses of omega-3 PUFAs on gut microbiota.In this study, we focus on the effects of different doses of omega-3 PUFAs on gut microbiota and immunity.OBJECTIVEIn this study, we focus on the effects of different doses of omega-3 PUFAs on gut microbiota and immunity.BALB/c mice was first treated with ceftriaxone sodium for 7 days, and then they received saline or different doses of omega-3 PUFAs (30, 60 and 90 mg omega-3 PUFAs) via daily gavage for 21 days. Alterations of cecum microbiota; the tight junction proteins, zonula occludens 3 (ZO3) and occludin, in the ileal wall; serum lipopolysaccharide (LPS); Interleukin-10 (IL-10), interleukin-1β (IL-1β), and Tumour Necrosis Factor α (TNF-α) ; mucus SIgA levels were measured.DESIGNBALB/c mice was first treated with ceftriaxone sodium for 7 days, and then they received saline or different doses of omega-3 PUFAs (30, 60 and 90 mg omega-3 PUFAs) via daily gavage for 21 days. Alterations of cecum microbiota; the tight junction proteins, zonula occludens 3 (ZO3) and occludin, in the ileal wall; serum lipopolysaccharide (LPS); Interleukin-10 (IL-10), interleukin-1β (IL-1β), and Tumour Necrosis Factor α (TNF-α) ; mucus SIgA levels were measured.Compared with the ceftriaxone sodium administration group, significant increases in bacterial richness and diversity were observed in the 60- and 90-mg omega-3 PUFA groups, while only a slight increase was observed in the 30-mg omega-3 PUFA group. A higher percentage of several genera, including Lactobacillus, Helicobacter, and Ruminococcus, and a lower percentage of Bacteroides, Clostridium, and Prevotella were observed in the 60- and 90-mg omega-3 PUFA groups when compared with those in the 30-mg group. The expression of ZO3 and occludin proteins increased in 60- and 90-mg omega-3 PUFA groups compared with the natural recovery group. The mucus SIgA and serum IL-10 levels were increased, and serum levels of LPS, IL-1β, and TNF-α were decreased in the 60- and 90-mg omega-3 PUFA groups when compared with those in the ceftriaxone sodium-treated group.RESULTSCompared with the ceftriaxone sodium administration group, significant increases in bacterial richness and diversity were observed in the 60- and 90-mg omega-3 PUFA groups, while only a slight increase was observed in the 30-mg omega-3 PUFA group. A higher percentage of several genera, including Lactobacillus, Helicobacter, and Ruminococcus, and a lower percentage of Bacteroides, Clostridium, and Prevotella were observed in the 60- and 90-mg omega-3 PUFA groups when compared with those in the 30-mg group. The expression of ZO3 and occludin proteins increased in 60- and 90-mg omega-3 PUFA groups compared with the natural recovery group. The mucus SIgA and serum IL-10 levels were increased, and serum levels of LPS, IL-1β, and TNF-α were decreased in the 60- and 90-mg omega-3 PUFA groups when compared with those in the ceftriaxone sodium-treated group.Different doses of omega-3 PUFAs have different therapeutic effects on the intestinal microbiota. The 60- and 90-mg omega-3 PUFA supplementation had better recovery effects on the gut microbiota and immunity than those of the 30 mg omega-3 PUFAs supplementation.CONCLUSIONDifferent doses of omega-3 PUFAs have different therapeutic effects on the intestinal microbiota. The 60- and 90-mg omega-3 PUFA supplementation had better recovery effects on the gut microbiota and immunity than those of the 30 mg omega-3 PUFAs supplementation.