Porphyromonas gingivalis promote microglia M1 polarization through the NF-кB signaling pathway.

Background: Porphyromonas gingivalis (P.gingivalis) is associated with the onset of Alzheimer's disease (AD), but the underlying molecular mechanism is unclear. Neuroinflammation in the brain from the microglial immune response induces the pathological progression of AD. In this study, the roles and molecular mechanism of P.gingivalis in microglial inflammation in vitro were investigated. Methods: In this study, a P.gingivalis oral administration mouse model was generated, and microglia were stimulated with P.gingivalis in vitro. The viability of the microglia after P.gingivalis treatment was evaluated through CCK-8 and live/dead cell staining. Inflammation in brain tissue after P.gingivalis treatment and the immune response of microglia in vitro were detected by RT‒PCR, Western blotting and IF. Moreover, the RNA sequence was used, and the role of the NF-κB signalling pathway in microglial activation was analysed after P.gingivalis stimulation. Results: The mRNA and protein levels of IL-6 and IL-17 were increased, and the expression of IL-10 was decreased in brain tissue after P.gingivalis oral administration. The viability of the HMC3 cells significantly decreased with 5% P.gingivalis after stimulation. The results of live/dead cell staining also showed the inhibitory effect of 5% P.gingivalis supplementation on cell viability. Moreover, 5% P.gingivalis supplementation increased the mRNA and protein levels of IL-6 and IL-17 and decreased IL-10 expression in HMC3 cells. P.gingivalis supplementation increased the mRNA and protein levels of iNOS and CD86 and decreased CD206 expression in HMC3 cells. RNA sequencing revealed that the NF-κB signalling pathway was involved in this process. Furthermore, p-P65 was upregulated and p-IKBα was downregulated in brain tissue and HMC3 cells after P.gingivalis stimulation, and an NF-κB signalling pathway inhibitor (QNZ) reversed the viability, M1 polarization and inflammatory factors of microglia in HMC3 cells in vitro. Conclusions: In conclusion, P.gingivalis induced neuroinflammation in the brain, possibly through promotion of M1 polarization of microglia via activation of the NF-κB signalling pathway during the progression of AD.

Assessment of Vibrionaceae prevalence in seafood from Qidong market and analysis of Vibrio parahaemolyticus strains.

The aim of this study was to investigate the prevalence of Vibrionaceae family in retail seafood products available in the Qidong market during the summer of 2023 and to characterize Vibrio parahaemolyticus isolates, given that this bacterium is the leading cause of seafood-associated food poisoning. We successfully isolated a total of 240 Vibrionaceae strains from a pool of 718 seafood samples. The breakdown of the isolates included 146 Photobacterium damselae, 59 V. parahaemolyticus, 18 V. campbellii, and 11 V. alginolyticus. Among these, P. damselae and V. parahaemolyticus were the predominant species, with respective prevalence rates of 20.3% and 8.2%. Interestingly, all 59 isolates of V. parahaemolyticus were identified as non-pathogenic. They demonstrated proficiency in swimming and swarming motility and were capable of forming biofilms across a range of temperatures. In terms of antibiotic resistance, the V. parahaemolyticus isolates showed high resistance to ampicillin, intermediate resistance to cefuroxime and cefazolin, and were sensitive to the other antibiotics evaluated. The findings of this study may offer valuable insights and theoretical support for enhancing seafood safety measures in Qidong City.

Revolutionizing early Alzheimer's disease and mild cognitive impairment diagnosis: a deep learning MRI meta-analysis.

BACKGROUND: The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a significant challenge in neurology, with conventional methods often limited by subjectivity and variability in interpretation. Integrating deep learning with artificial intelligence (AI) in magnetic resonance imaging (MRI) analysis emerges as a transformative approach, offering the potential for unbiased, highly accurate diagnostic insights. OBJECTIVE: A meta-analysis was designed to analyze the diagnostic accuracy of deep learning of MRI images on AD and MCI models. METHODS: A meta-analysis was performed across PubMed, Embase, and Cochrane library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, focusing on the diagnostic accuracy of deep learning. Subsequently, methodological quality was assessed using the QUADAS-2 checklist. Diagnostic measures, including sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUROC) were analyzed, alongside subgroup analyses for T1-weighted and non-T1-weighted MRI. RESULTS: A total of 18 eligible studies were identified. The Spearman correlation coefficient was -0.6506. Meta-analysis showed that the combined sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.84, 0.86, 6.0, 0.19, and 32, respectively. The AUROC was 0.92. The quiescent point of hierarchical summary of receiver operating characteristic (HSROC) was 3.463. Notably, the images of 12 studies were acquired by T1-weighted MRI alone, and those of the other 6 were gathered by non-T1-weighted MRI alone. CONCLUSION: Overall, deep learning of MRI for the diagnosis of AD and MCI showed good sensitivity and specificity and contributed to improving diagnostic accuracy.

ANTECEDENTES: O diagnóstico precoce da doença de Alzheimer (DA) e do comprometimento cognitivo leve (CCL) continua sendo um desafio significativo na neurologia, com métodos convencionais frequentemente limitados pela subjetividade e variabilidade na interpretação. A integração da aprendizagem profunda com a inteligência artificial (IA) na análise de imagens de ressonância magnética surge como uma abordagem transformadora, oferecendo o potencial para insights diagnósticos imparciais e altamente precisos. OBJETIVO: Uma metanálise foi projetada para analisar a precisão diagnóstica do aprendizado profundo de imagens de ressonância magnética em modelos de DA e CCL. MéTODOS: Uma metanálise foi realizada nos bancos de dados das bibliotecas PubMed, Embase e Cochrane seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), com foco na precisão diagnóstica do aprendizado profundo. Posteriormente, a qualidade metodológica foi avaliada por meio do checklist QUADAS-2. Medidas diagnósticas, incluindo sensibilidade, especificidade, razões de verossimilhança, razão de chances diagnósticas e área sob a curva característica de operação do receptor (area under the receiver operating characteristic curve [AUROC]) foram analisadas, juntamente com análises de subgrupo para ressonância magnética ponderada em T1 e não ponderada em T1. RESULTADOS: Um total de 18 estudos elegíveis foram identificados. O coeficiente de correlação de Spearman foi de -0,6506. A metanálise mostrou que a sensibilidade e a especificidade combinadas, a razão de verossimilhança positiva, a razão de verossimilhança negativa e a razão de chances de diagnóstico foram 0,84, 0,86, 6,0, 0,19 e 32, respectivamente. A AUROC foi de 0,92. O ponto quiescente do resumo hierárquico da característica de operação do receptor (hierarchical summary of receiver operating characteristic [HSROC]) foi 3,463. Notavelmente, as imagens de 12 estudos foram adquiridas apenas por ressonância magnética ponderada em T1, e as dos outros 6 foram obtidas apenas por ressonância magnética não ponderada em T1. CONCLUSãO: Em geral, a aprendizagem profunda da ressonância magnética para o diagnóstico de DA e CCL mostrou boa sensibilidade e especificidade e contribuiu para melhorar a precisão diagnóstica.

Characterizing human spontaneous thoughts and its application in major depressive disorder.

BACKGROUND: Spontaneous thought is a universal, complex, and heterogeneous cognitive activity that significantly impacts mental activity and strongly correlates with mental disorders. METHODS: Utilizing the think-aloud method, we captured spontaneous thoughts during rest from 38 diagnosed with depression, alongside 36 healthy controls and 137 healthy individuals. Through a comprehensive assessment of various dimensions of thought content, we compared thought content between individuals with depression and healthy controls, and between healthy women and men. Finally, we employed natural language processing (NLP) to develop regression models for multidimensional content assessment and a classification model to differentiate between individuals with and without depression. RESULTS: Compared to healthy controls, individuals with depression had more internally oriented and less externally oriented spontaneous thoughts. They focused more on themselves and negative things, and less on positive things, experiencing higher levels of negative emotions and lower levels of positive emotions. Besides, we found that compared to healthy men, healthy women's spontaneous thoughts focus more on interoception, the self, past events, and negative events, and they experience higher levels of negative emotions. Meanwhile, we identified the potential application of the think-aloud method to collect spontaneous thoughts and integrate NLP in the field of depression. CONCLUSIONS: This study offers direct insights into the stream of thought during individuals' resting state, revealing differences between individuals with depression and healthy controls, as well as sex differences in the content of spontaneous thoughts. It enhances our understanding of spontaneous thought and offers a new perspective for preventing, diagnosing, and treating depression.

Bioinspired Flexible Kevlar/Hydrogel Composites with Antipuncture and Strain-Sensing Properties for Personal Protective Equipment.

Currently, multifunction has become an essential direction of personal protective equipment (PPE), but achieving the protective effect, flexibility, physiological comfort, and intelligent application of PPE simultaneously is still a challenge. Herein, inspired by the meso-structure of rhinoceros skin, a novel strategy is proposed by compounding an ammonium sulfate ((NH4)2SO4) solution soaked gelatin hydrogel with the high weight fraction and vertically interwoven Kevlar fibers to manufacture a flexible and wearable composite with enhanced puncture resistance and strain-sensing properties. After (NH4)2SO4 solution immersion, the hydrogel's tensile strength, toughness, and fracture strain were up to 3.77 MPa, 4.26 MJ/m3, and 305.19%, respectively, indicating superior mechanical properties. The Kevlar/hydrogel composites revealed excellent puncture resistance (quasi-static of 132.06 N and dynamic of 295.05 N), flexibility (138.13 mN/cm), and air and moisture permeability (17.83 mm/s and 2092.73 g m-2 day-1), demonstrating a favorable balance between the protective effect and wearing comfort even after 7 days of environmental exposure. Meanwhile, salt solution immersion endowed the composite with excellent strain-sensing properties at various bending angles (30-90°) and frequencies (0.25-1 Hz) and allowed it to monitor different human motions directly in real-time. The rhinoceros-skin-inspired Kevlar/hydrogel composites provide a simple and economical solution for antipuncture materials that combine high protective effects, a comfortable wearing experience, and good strain-sensing properties, promising multifunctional PPE in the future.

Rapid phenotypic and genotypic change in a laboratory schistosome population.

Background: Genomic analysis has revealed extensive contamination among laboratory-maintained microbes including malaria parasites, Mycobacterium tuberculosis and Salmonella spp. Here, we provide direct evidence for recent contamination of a laboratory schistosome parasite population, and we investigate its genomic consequences. The Brazilian Schistosoma mansoni population SmBRE has several distinctive phenotypes, showing poor infectivity, reduced sporocysts number, low levels of cercarial shedding and low virulence in the intermediate snail host, and low worm burden and low fecundity in the vertebrate rodent host. In 2021 we observed a rapid change in SmBRE parasite phenotypes, with a ∼10x increase in cercarial production and ∼4x increase in worm burden. Methods: To determine the underlying genomic cause of these changes, we sequenced pools of SmBRE adults collected during parasite maintenance between 2015 and 2023. We also sequenced another parasite population (SmLE) maintained alongside SmBRE without phenotypic changes. Results: While SmLE allele frequencies remained stable over the eight-year period, we observed sudden changes in allele frequency across the genome in SmBRE between July 2021 and February 2023, consistent with expectations of laboratory contamination. (i) SmLE-specific alleles rose in the SmBRE population from 0 to 41-46% across the genome between September and October 2021, documenting the timing and magnitude of the contamination event. (ii) After contamination, strong selection ( s = ∼0.23) drove replacement of low fitness SmBRE with high fitness SmLE alleles. (iii) Allele frequency changed rapidly across the whole genome, except for a region on chromosome 4 where SmBRE alleles remained at high frequency. Conclusions: We were able to detect contamination in this case because SmBRE shows distinctive phenotypes. However, this would likely have been missed with phenotypically similar parasites. These results provide a cautionary tale about the importance of tracking the identity of parasite populations, but also showcase a simple approach to monitor changes within populations using molecular profiling of pooled population samples to characterize fixed single nucleotide polymorphisms. We also show that genetic drift results in continuous change even in the absence of contamination, causing parasites maintained in different labs (or sampled from the same lab at different times) to diverge.

Association between kidney function and Parkinson's disease risk: a prospective study from the UK Biobank.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative influenced by various clinical factors. The potential relationship between renal function and the risk of PD remains poorly understood. This study aims to explore the association between kidney function and the risk of developing PD. METHODS: A population-based cohort study was conducted using data from 400,571 UK Biobank participants. Renal function was assessed using the estimated glomerular filtration rate (eGFR), calculated from serum creatinine and cystatin C levels. The association between eGFR levels and PD risk was evaluated using univariate and multivariate Cox regression analyses, Restricted Cubic Spline (RCS) analysis, and Kaplan-Meier analysis. Additionally, a clinical prediction model was developed and its diagnostic accuracy was evaluated using ROC analysis. A heatmap was also constructed to examine the relationship between clinical factors and gray matter volume in various brain regions. RESULTS: Over a median observation period of 13.8 years, 2740 PD events were recorded. Cox regression and Kaplan-Meier analyses revealed a significant association between decreased eGFR and increased PD risk, particularly in participants with eGFR < 30 ml/min/1.73 m2. This association was confirmed across three adjusted models. RCS analysis demonstrated a nonlinear relationship between decreasing eGFR and increasing PD risk. Furthermore, changes in eGFR were correlated with alterations in subcortical gray matter volume in regions such as the frontal cortex, striatum, and cerebellum. The clinical prediction model showed high diagnostic accuracy with AUC values of 0.776, 0.780, and 0.824 for 4-, 8-, and 16-year predictions, respectively. CONCLUSION: Renal insufficiency is significantly associated with an increased risk of PD, highlighting the importance of maintaining good kidney function as a potential preventive measure against PD.

The additive effect of the triglyceride-glucose index and estimated glucose disposal rate on long-term mortality among individuals with and without diabetes: a population-based study.

BACKGROUND: The triglyceride-glucose (TyG) index and estimated glucose disposal rate (eGDR), which are calculated using different parameters, are widely used as markers of insulin resistance and are associated with cardiovascular diseases and prognosis. However, whether they have an additive effect on the risk of mortality remains unclear. This study aimed to explore whether the combined assessment of the TyG index and eGDR improved the prediction of long-term mortality in individuals with and without diabetes. METHODS: In this cross-sectional and cohort study, data were derived from the National Health and Nutrition Examination Survey (NHANES) 2001-2018, and death record information was obtained from the National Death Index. The associations of the TyG index and eGDR with all-cause and cardiovascular mortality were determined by multivariate Cox regression analysis and restricted cubic splines. RESULTS: Among the 17,787 individuals included in the analysis, there were 1946 (10.9%) all-cause deaths and 649 (3.6%) cardiovascular deaths during a median follow-up of 8.92 years. In individuals with diabetes, the restricted cubic spline curves for the associations of the TyG index and eGDR with mortality followed a J-shape and an L-shape, respectively. The risk of mortality significantly increased after the TyG index was > 9.04 (all-cause mortality) or > 9.30 (cardiovascular mortality), and after eGDR was < 4 mg/kg/min (both all-cause and cardiovascular mortality). In individuals without diabetes, the association between eGDR and mortality followed a negative linear relationship. However, there was no association between the TyG index and mortality. Compared with individuals in the low TyG and high eGDR group, those in the high TyG and low eGDR group (TyG > 9.04 and eGDR < 4) showed the highest risk for all-cause mortality (hazard ratio [HR] = 1.592, 95% confidence interval [CI] 1.284-1.975) and cardiovascular mortality (HR = 1.683, 95% CI 1.179-2.400) in the overall population. Similar results were observed in individuals with and without diabetes. CONCLUSIONS: There was a potential additive effect of the TyG index and eGDR on the risk of long-term mortality in individuals with and without diabetes, which provided additional information for prognostic prediction and contributed to improving risk stratification.

Fatal multiple acyl-CoA dehydrogenase deficiency caused by ETFDH gene mutation: A case report.

BACKGROUND: Multiple acyl-CoA dehydrogenase deficiency (MADD) is a disease of rare autosomal recessive disorder. There are three types of MADD. Type I is a neonatal-onset form with congenital anomalies. Type II is a neonatal-onset form without congenital anomalies. Type III is considered to a milder form and usually responds to riboflavin. However, late-onset form could also be fatal and not responsive to treatments. CASE SUMMARY: We report a severe case of a young man with onset type III MADD induced by drugs and strenuous exercise characterized by rhabdomyolysis and liver dysfunction. Urine analysis indicated 12 out of 70 kinds of organic acids like glutaric acid-2 were detected. Serum analysis in genetic metabolic diseases revealed 24 out of 43 tested items were abnormal, revealing the elevation of several acylcarnitines and the reduction of carnitine in the patient. By next generation sequencing technology for gene sequencing related to fatty acid oxidation and carnitine cycle defects, a rare ETFDH gene variant was identified: NM_004453:4:C.1448C>T(p.Pro483 Leu). The patient was diagnosed with late-onset GAII. He was not responsive to riboflavin and progressively worsened into multiple organ failure that finally led to death. CONCLUSION: Type III MADD can also be fatal and not responsive to treatments.

Hydrogel dressings on neurotrophic keratitis in an experimental animal model.

AIM: To investigate the therapeutic effects of hydrogel dressings on neurotrophic keratitis in rats. METHODS: Male Wistar rats, aged 42-56d, were randomly divided into control, experimental, and treatment groups, each consisting of five rats. The experimental and treatment groups underwent neurotrophic keratitis modeling in both eyes. After successful modeling, biomedical hydrogels formed with polyvinyl alcohol and polyvinyl pyrrolidone were used in treatment group for 7d. Ocular irritation response and keratitis index scores, Schirmer's test, tear film break-up time (BUT), sodium fluorescein staining, and hematoxylin and eosin (HE) staining were used to evaluate the effectiveness of the treatment. RESULTS: The neurotrophic keratitis model was successfully established in rats with severe ophthalmic nerve injury, characterized by keratitis, ocular irritation, reduced tear secretion measured by decreased BUT and Schirmer test values, corneal epithelial loss, and disorganized collagen fibers in the stromal layer. Following treatment with hydrogel dressings, significant improvements were observed in keratitis scores and ocular irritation symptoms in model eyes. Although the recovery of tear secretion, as measured by the Schirmer's test, did not show statistical differences, BUT was significantly prolonged. Fluorescein staining confirmed a reduction in the extent of corneal epithelial loss after treatment. HE staining revealed the restoration of the structural disorder in both the epithelial and stromal layers to a certain extent. CONCLUSION: Hydrogel dressing reduces ocular surface irritation, improves tear film stability, and promotes the repair and restoration of damaged epithelial cells by maintaining a moist and clean environment on the ocular surface in the rat model.

Progress of research on the treatment of depression by traditional Chinese medicine prescriptions.

Depression is a common psychiatric disorder that belongs to the category of "Depression Syndrome" in traditional Chinese medicine (TCM), and its etiology and pathogenesis are complex and unclear. It is characterized by high prevalence, high disability rate, and high recurrence rate, which seriously affect human health, and its treatment has become a research hotspot worldwide. At present, the antidepressants commonly used in the clinic are mainly Western medicine (WM), but there are problems such as frequent side effects and poor efficacy. Studies have found that the use of TCM prescriptions in the treatment of depression can achieve the same effect as WM; and when TCM prescriptions are combined with WM, the efficacy can be enhanced while the adverse effects of WM can be reduced. Pharmacological studies related to the treatment of depression with traditional Chinese medicine prescriptions (TCMPs) have focused on the neurobiochemical system, gut microbes, and energy metabolism in mitochondria. No one has yet reviewed the pharmacological mechanism of TCMPs for depression. So, this paper reviews the pharmacological mechanism of TCMPs for depression from the perspective of TCMPs, introduces the progress of research on classical TCMPs for depression and their antidepressant mechanism. This article aims to promote the application of TCMPs in the clinic and provide a new therapeutic idea for the clinical treatment of depression.

Mast Cell Infiltration and Subtype Promote Malignant Transformation of Oral Precancer and Progression of Oral Cancer.

The role of mast cell (MC), a common myeloid-derived immune cell, in the development of oral squamous cell carcinoma (OSCC) is unclear. The aim of this study was to investigate MC infiltration in oral precancer and oral cancer. The evaluation of immune cell infiltration and its association with prognosis in OSCC used RNA sequencing and multiple public datasets. Multiplex immunofluorescence was used to explore the infiltration of MC in the microenvironment of OSCC and oral precancer and the interaction with CD8+ cells. The role of MC in OSCC progression was verified by in vivo experiments. The resting MC infiltration was mainly present in oral precancer, whereas activated MC infiltration was significantly higher in OSCC. Activated MC was associated with malignant transformation of oral precancer and poor prognosis of OSCC. In vivo studies showed that MC promoted the growth of OSCC. The infiltration of activated MC was negatively correlated with the infiltration of CD8+ T cells. The subtype of MC containing tryptase without chymase (MCT) was significantly higher in OSCC compared with oral precancer and was associated with poor survival. Furthermore, spatial distance analysis revealed a greater distance between MCT and CD8+ cells, which was also linked to poor prognosis in OSCC. Cox regression analysis showed that MCT could be a potential diagnostic and prognostic biomarker. This study provides new insights into the role of MC in the immune microenvironment of OSCC. It might enhance the immunotherapeutic efficacy of OSCC by developing targeted therapies against MC. SIGNIFICANCE: In this study, we investigated the role of mast cells (MC) in oral precancer and oral cancer and demonstrated that MCs are involved in oral cancer progression and may serve as a potential diagnostic and prognostic marker. It might improve the immunotherapeutic efficacy through developing targeted therapies against MCs.

Engineered mitochondria exert potent antitumor immunity as a cancer vaccine platform.

The preferable antigen delivery profile accompanied by sufficient adjuvants favors vaccine efficiency. Mitochondria, which feature prokaryotic characteristics and contain various damage-associated molecular patterns (DAMPs), are easily taken up by phagocytes and simultaneously activate innate immunity. In the current study, we established a mitochondria engineering platform for generating antigen-enriched mitochondria as cancer vaccine. Ovalbumin (OVA) and tyrosinase-related protein 2 (TRP2) were used as model antigens to synthesize fusion proteins with mitochondria-localized signal peptides. The lentiviral infection system was then employed to produce mitochondrial vaccines containing either OVA or TRP2. Engineered OVA- and TRP2-containing mitochondria (OVA-MITO and TRP2-MITO) were extracted and evaluated as potential cancer vaccines. Impressively, the engineered mitochondria vaccine demonstrated efficient antitumor effects when used as both prophylactic and therapeutic vaccines in murine tumor models. Mechanistically, OVA-MITO and TRP2-MITO potently recruited and activated dendritic cells (DCs) and induced a tumor-specific cell-mediated immunity. Moreover, DC activation by mitochondria vaccine critically involves TLR2 pathway and its lipid agonist, namely, cardiolipin derived from the mitochondrial membrane. The results demonstrated that engineered mitochondria are natively well-orchestrated carriers full of immune stimulants for antigen delivery, which could preferably target local dendritic cells and exert strong adaptive cellular immunity. This proof-of-concept study established a universal platform for vaccine construction with engineered mitochondria bearing alterable antigens for cancers as well as other diseases.

Deciphering breast cancer prognosis: a novel machine learning-driven model for vascular mimicry signature prediction.

Background: In the ongoing battle against breast cancer, a leading cause of cancer-related mortality among women globally, the urgent need for innovative prognostic markers and therapeutic targets is undeniable. This study pioneers an advanced methodology by integrating machine learning techniques to unveil a vascular mimicry signature, offering predictive insights into breast cancer outcomes. Vascular mimicry refers to the phenomenon where cancer cells mimic blood vessel formation absent of endothelial cells, a trait associated with heightened tumor aggression and diminished response to conventional treatments. Methods: The study's comprehensive analysis spanned data from over 6,000 breast cancer patients across 12 distinct datasets, incorporating both proprietary clinical data and single-cell data from 7 patients, accounting for a total of 43,095 cells. By employing an integrative strategy that utilized 10 machine learning algorithms across 108 unique combinations, the research scrutinized 100 existing breast cancer signatures. Empirical validation was sought through immunohistochemistry assays, alongside explorations into potential immunotherapeutic and chemotherapeutic avenues. Results: The investigation successfully identified six genes related to vascular mimicry from multi-center cohorts, laying the groundwork for a novel predictive model. This model outstripped the prognostic accuracy of traditional clinical and molecular indicators in forecasting recurrence and mortality risks. High-risk individuals identified by our model faced worse outcomes. Further validation through IHC assays in 30 patients underscored the model's extensive applicability. Notably, the model unveiled varying therapeutic responses; low-risk patients might achieve greater benefits from immunotherapy, whereas high-risk patients demonstrated a particular sensitivity to certain chemotherapies, such as ispinesib. Conclusions: This model marks a significant step forward in the precise evaluation of breast cancer prognosis and therapeutic responses across different patient groups. It heralds the possibility of refining patient outcomes through tailored treatment strategies, accentuating the potential of machine learning in revolutionizing cancer prognosis and management.

The uncertainties and certainties of gene transcription in a human tumor cell.

Previously we have identified that the expression number and levels of oncogenes and antioncogenes are highly positively or negatively associated with major cellular progress in a cancer cell. However, we have not defined any cellular potentials of a human tumor cell at the level of the overall gene expression. Here, we counted the overall number of expression genes and overall counts of mRNA in depth and revealed that the expression levels of mRNA were directly associated with the expression number of genes in a human tumor cell. Gene expression networks revealed steady states of tricarboxylic acid (TCA) cycle and ATP production, differentiation potentials that might be disturbed and blocked by uncertain gene expressing networks, and potential capabilities to undergo epithelial-mesenchymal transition (EMT), neurogenesis, angiogenesis, inflammatory response, immune evasion, and metastasis in a human tumor cell. Our analysis identifies unpredictable gene expression characteristics in human tumor cells. The results might profoundly influence mechanisms how a human tumor cell generates and undergoes its progresses.

Origin of Manipulating Selectivity in Prins Cyclization by [Ga4L6]12- Supramolecular Catalysis through Host-Guest Interactions.

The host effect of the supramolecular [Ga4L6]12- tetrahedral metallocage on Prins cyclization reaction of the substrate by encapsulated citronellal has been investigated by means of molecular dynamics and quantum mechanics. The encapsulation process of the substrate into the [Ga4L6]12- cavity was simulated via attach-pull-release (APR) methods. Thermodynamic calculations and classical molecular dynamics simulations assessed the substrate's microenvironment inside the cavity, guiding DFT-level modeling of the reaction. DFT calculations show diol product predominance in acidic solution but high enol selectivity inside [Ga4L6]12-, consistent with experimental findings. [Ga4L6]12- alters the selectivity of the Prins cyclization reaction by inhibiting diol formation. The activation strain model-based decomposition analysis (ASM-DA) of the barrier difference among distortion and interaction terms indicates that the more positive interaction between a host and guest in the diol transition state than enol determines the product selectivity, particularly the fewer C-H···O and O-H···O hydrogen-bonding interactions. These theoretical insights could contribute to a deeper understanding of the nature of supramolecular catalysis and to further develop new supramolecular catalysts.

Assessment of indoor light-at-night exposure in children and adolescents during schooldays and weekends.

Light-At-Night (LAN) is increasingly recognized and may has adverse health effects on children and adolescents, yet few studies have reported objective indoor LAN exposure levels for children and adolescents. In this study, we measured the indoor LAN exposure levels and duration among 897 children and adolescents aged 6-14 in Beijing, China, using portable photometers during both school days and weekends. Results indicate that the median indoor LAN exposure from 9:00 p.m. to 7:00 a.m. was 5.1 lx, with 31.8% of the subjects experiencing an average exposure above 10 lx. Additionally, from the perspective of cumulative high exposure duration, children and adolescents were exposed to more than 10 lx for approximately 64 min from 9:00 p.m. to 7:00 a.m. During the entire nighttime (from self-reported bedtime to wake-up time), the median exposure was 2.1 lx, with 16.6% averaging exposures above 10 lx. Exposure levels were significantly higher on weekends than on schooldays. Both girls and upper-grade students had higher levels of exposure and longer durations of high exposure. Girls in grade 7 (OR:2.56, 95%CI: 1.68-3.88) experienced the highest LAN exposure in our subjects compared to boys in grade 1-4. Our findings underscore the importance of promoting healthy light exposure behaviors among children and adolescents and reducing their light exposure environments to mitigate the potential health impacts of LAN.

Prdm1 positively regulates liver Group 1 ILCs cancer immune surveillance and preserves functional heterogeneity.

Group 1 innate lymphoid cells (ILCs) comprise conventional natural killer (cNK) cells and type 1 innate lymphoid cells (ILC1s). The main functions of liver cNK cells and ILC1s not only include directly killing target cells but also regulating local immune microenvironment of the liver through the secretion of cytokines. Uncovering the intricate mechanisms by which transcriptional factors regulate and influence the functions of liver cNK cells and ILC1s, particularly within the context of liver tumors, presents a significant opportunity to amplify the effectiveness of immunotherapies against liver malignancies. Using Ncr1-drived conditional knockout mouse model, our study reveals the regulatory role of Prdm1 in shaping the composition and maturation of cNK cells. Although Prdm1 did not affect the killing function of cNK cells in an in vivo cytotoxicity model, a significant increase in cancer metastasis was observed in Prdm1 knockout mice. Interferon-gamma (IFN-γ), granzyme B, and perforin secretion decreased significantly in Prdm1-deficient cNK cells and liver ILC1s. Single-cell RNA sequencing (scRNA-seq) data also provided evidences that Prdm1 maintains functional subsets of cNK cells and liver ILC1s and facilitates communications between cNK cells, liver ILC1s, and macrophages. The present study unveiled a novel regulatory mechanism of Prdm1 in cNK cells and liver ILC1s, showing promising potential for developing innovative immune therapy strategies against liver cancer.

The PRMT6/STAT1/ACSL1 axis promotes ferroptosis in diabetic nephropathy.

Hyperglycaemia-induced ferroptosis is a significant contributor to kidney dysfunction in diabetic nephropathy (DN) patients. In addition, targeting ferroptosis has clinical implications for the treatment of DN. However, effective therapeutic targets for ferroptosis have not been identified. In this study, we aimed to explore the precise role of protein arginine methyltransferase 6 (PRMT6) in regulating ferroptosis in DN. In the present study, we utilized a mouse DN model consisting of both wild-type and PRMT6-knockout (PRMT6-/-) mice. Transcriptomic and lipidomic analyses, along with various molecular biological methodologies, were used to determine the potential mechanism by which PRMT6 regulates ferroptosis in DN. Our results indicate that PRMT6 downregulation participates in kidney dysfunction and renal cell death via the modulation of ferroptosis in DN. Moreover, PRMT6 reduction induced lipid peroxidation by upregulating acyl-CoA synthetase long-chain family member 1 (ACSL1) expression, ultimately contributing to ferroptosis. Furthermore, we investigated the molecular mechanism by which PRMT6 interacts with signal transducer and activator of transcription 1 (STAT1) to jointly regulate ACSL1 transcription. Additionally, treatment with the STAT1-specific inhibitor fludarabine delayed DN progression. Furthermore, we observed that PRMT6 and STAT1 synergistically regulate ACSL1 transcription to mediate ferroptosis in hyperglycaemic cells. Our study demonstrated that PRMT6 and STAT1 comodulate ACSL1 transcription to induce the production of phospholipid-polyunsaturated fatty acids (PL-PUFAs), thus participating in ferroptosis in DN. These findings suggest that the PRMT6/STAT1/ACSL1 axis is a new therapeutic target for the prevention and treatment of DN.