A three-stage wavelength selection algorithm for near-infrared spectroscopy calibration.

The near-infrared spectral data is highly high dimensional and contains redundant information, it is necessary to identify the most representative characteristic wavelengths before modeling to improve model accuracy and reliability. At present, there are many methods for selecting the characteristic wavelengths of NIR spectroscopy, but the collinearity among wavelengths is still a main issue that leads to poor model effects. Therefore, this study proposes a three-stage wavelength selection algorithm (Stage III) to reduce redundancy in NIR spectral data and collinearity between wavelength variables, resulting in a simpler and more accurate predictive model. The research uses a public NIR data set of corn samples as its subject. Initially, the wavelengths with the higher correlation coefficients are chosen after calculating the relationship coefficients between every wavelength vector and the concentration vector. On this basis, the correlation coefficients between the vectors of each wavelength point are calculated, and those wavelength points with smaller correlation coefficients with other wavelength points are selected. Ultimately, the stepwise regression analysis selects the wavelengths that provide substantial value to the model as the variables for modeling, leading to the development of a multiple linear regression model. The results show that the model using the three-stage wavelength selection algorithm outperforms those using the full spectrum, Stages I and Stage II, and the coefficient of determination of the test set of the Stage III-MLR model achieved an accuracy of 0.9360. Instead of the successive projections algorithm (SPA), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS), Stage III is better in the model prediction accuracy. Therefore, the three-stage wavelength selection algorithm is an effective wavelength selection algorithm that can effectively model NIR spectroscopy, reduce the collinearity between the wavelength variables, simplify the complexity of the model, and improve the prediction precision of the model.

Regulating the zinc ion transport kinetics of Mn3O4 through copper doping towards high-capacity aqueous Zn-ion battery.

High working voltage, large theoretical capacity and cheapness render Mn3O4 promising cathode candidate for aqueous zinc ion batteries (AZIBs). Unfortunately, poor electrochemical activity and bad structural stability lead to low capacity and unsatisfactory cycling performance. Herein, Mn3O4 material was fabricated through a facile precipitation reaction and divalent copper ions were introduced into the crystal framework, and ultra-small Cu-doped Mn3O4 nanocrystalline cathode materials with mixed valence states of Mn2+, Mn3+ and Mn4+ were obtained via post-calcination. The presence of Cu acts as structural stabilizer by partial substitution of Mn, as well as enhance the conductivity and reactivity of Mn3O4. Significantly, based on electrochemical investigations and ex-situ XPS characterization, a synergistic effect between copper and manganese was revealed in the Cu-doped Mn3O4, in which divalent Cu2+ can catalyze the transformation of Mn3+ and Mn4+ to divalent Mn2+, accompanied by the translation of Cu2+ to Cu0 and Cu+. Benefitting from the above advantages, the Mn3O4 cathode doped with moderate copper (abbreviated as CMO-2) delivers large discharge capacity of 352.9 mAh g-1 at 100 mA g-1, which is significantly better than Mn3O4 (only 247.8 mAh g-1). In addition, CMO-2 holds 203.3 mAh g-1 discharge capacity after 1000 cycles at 1 A g-1 with 98.6 % retention, and after 1000 cycles at 5 A g-1, it still performs decent discharge capacity of 104.2 mAh g-1. This work provides new ideas and approaches for constructing manganese-based AZIBs with long lifespan and high capacity.

Toxic Metals and Metalloids in Food: Current Status, Health Risks, and Mitigation Strategies.

PURPOSE OF REVIEW: Exposure to toxic metals/metalloids, such as arsenic (As), cadmium (Cd), and lead (Pb), through food consumption is a global public health concern. This review examines the contamination status of these metals/metalloids in food, assesses dietary intake across different populations, and proposes strategies to reduce metal/metalloid exposures throughout the food chain. RECENT FINDINGS: For the general population, dietary intake of metals/metalloids is generally lower than health-based guidance values. However, for vulnerable populations, such as infants, children, and pregnant women, their dietary intake levels are close to or even higher than the guidance values. Among different food categories, seafood shows higher total As, but largely present as organic species. Rice accumulates higher As concentration than other cereals, with inorganic As (iAs) and dimethylarsinic acid (DMA) being the main As species. Methylated thioarsenate species, such as dimethylmonothioarsenate, have also been detected in rice. The distribution of iAs and DMA in rice shows geographical variation. Additionally, seafood and cocoa products generally contain more Cd than other food, but seafood consumption does not significantly increase in adverse health effects due to its high zinc and iron content. Compared to As and Cd, Pb concentrations in food are generally lower. To minimize the health risks of metal/metalloid exposure, several strategies are proposed. Food contamination with toxic metals/metalloids poses significant concerns for human health, particularly for vulnerable populations. This review provides scientific evidence and suggestions for policy makers to reduce human exposure of metals/metalloids via dietary intake.

An alternating copolymer of phenothiazine and ethylenedioxythiophene for perovskite solar cells: effects of flexible and rigid substituent alternation.

Developing p-type polymeric semiconductors with exceptional electrical performance, heat tolerance, and cost-effectiveness is pivotal for advancing the practical application of n-i-p perovskite solar cells. Here, we employed direct arylation polycondensation to synthesize an alternating copolymer of phenothiazine and 3,4-ethylenedioxythiophene, featuring a high glass transition temperature (175 °C). In addition to the alternation of conjugated units within the main chain, the copolymer features alternating flexible (2-octyldodecyl) and rigid (trimethylphenyl) substituents at the nitrogen positions of the phenothiazine moiety. Compared to reference polymers with solely flexible or rigid substituents, the alternating use of these moieties resulted in the polymeric semiconductor composite film with smoother morphology and enhanced hole mobility. By employing this polymer with a distinct distribution of substituents and an innovative main chain structure as a hole transport material, we fabricated perovskite solar cells achieving an average efficiency of 25.1%. These cells also exhibited excellent stabilities under conditions of 85 °C thermal storage and 45 °C operation.

Photoconductivity and Photovoltaic Effect Strengthened via Microstructural Cotuning in Ferroelectrics: Intuitively Assessed by Macroscopic Transparency.

Photoferroelectrics that involve strong light-matter coupling are regarded as promising candidates for realizing bulk photovoltaic and photoelectric effects via light absorption. Nonetheless, understanding the photoresponse mechanism or modulation of performance from a microscopic point of view is scarcely explored through quantification of macroscopic properties. Herein, we design a model material, Gd3+-doped (K0.5Na0.5)NbO3 ferroelectric-transparent ceramics, and present an advantageous strategy to enhance the optoelectronic coupling through joint modulations of lattice distortion and oxygen vacancies, along with inner defects and ferroelectric domains. Significantly, their microcosmic manipulation can be intuitively and facilely evaluated by the optical transparency of each ceramic. An approximately 104 fold increase in conductivity under ultraviolet irradiation was produced. Under the cocoupling between external physical fields, the synergy of photoelectric stimulation increased the photoconductivity of the ceramics by 13.89 times. Additionally, a significant increase (4.5-fold) in the current output from the photovoltaic effect was achieved via ferroelectric domains of moderate size, whose size could be easily assessed by optical transmittance. In situ microscopic observations confirmed that the configuration of oxygen vacancy-dependent ferroelectric domains contributes to the enhanced optoelectronic response. This research provides a distinct way to develop inexpensive optocoupler devices and meet the requirements for multifunctional integration in single photoferroelectrics.

Coordinated NREM sleep oscillations among hippocampal subfields modulate synaptic plasticity in humans.

The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.

Prolonged Omicron-Specific B Cell Maturation Alleviates Immune Imprinting Induced by SARS-CoV-2 Inactivated Vaccine.

SARS-CoV-2 ancestral strain-induced immune imprinting poses great challenges to updating vaccines for new variants. Studies showed that repeated Omicron exposures could override immune imprinting induced by inactivated vaccines but not mRNA vaccines, a disparity yet to be understood. Here, we analyzed the immune imprinting alleviation in inactivated vaccine (CoronaVac) cohorts after a long-term period following breakthrough infections (BTI). We observed in CoronaVac-vaccinated individuals who experienced BA.5/BF.7 BTI, the proportion of Omicron-specific memory B cells (MBCs) substantially increased after an extended period post-Omicron BTI, with their antibodies displaying enhanced somatic hypermutation and neutralizing potency. Consequently, the neutralizing antibody epitope distribution encoded by MBCs post-BA.5/BF.7 BTI after prolonged maturation closely mirrors that in BA.5/BF.7-infected unvaccinated individuals. Together, these results indicate the activation and expansion of Omicron-specific naïve B cells generated by first-time Omicron exposure helped to alleviate CoronaVac-induced immune imprinting, and the absence of this process should have caused the persistent immune imprinting seen in mRNA vaccine recipients.

Omicron-specific ultra-potent SARS-CoV-2 neutralizing antibodies targeting the N1/N2 loop of Spike N-terminal domain.

A multitude of functional mutations continue to emerge on the N-terminal domain (NTD) of the spike protein in SARS-CoV-2 Omicron subvariants. Understanding the immunogenicity of Omicron NTD and the properties of antibodies elicited by it is crucial for comprehending the impact of NTD mutations on viral fitness and guiding vaccine design. In this study, we find that most of NTD-targeting antibodies isolated from individuals with BA.5/BF.7 breakthrough infection (BTI) are ancestral (wildtype or WT)-reactive and non-neutralizing. Surprisingly, we identified five ultra-potent neutralizing antibodies (NAbs) that can only bind to Omicron but not WT NTD. Structural analysis revealed that they bind to a unique epitope on the N1/N2 loop of NTD and interact with the receptor-binding domain (RBD) via the light chain. These Omicron-specific NAbs achieve neutralization through ACE2 competition and blockage of ACE2-mediated S1 shedding. However, BA.2.86 and BA.2.87.1, which carry insertions or deletions on the N1/N2 loop, can evade these antibodies. Together, we provided a detailed map of the NTD-targeting antibody repertoire in the post-Omicron era, demonstrating their vulnerability to NTD mutations enabled by its evolutionary flexibility, despite their potent neutralization. These results revealed the function of the indels in the NTD of BA.2.86/JN.1 sublineage in evading neutralizing antibodies and highlighted the importance of considering the immunogenicity of NTD in vaccine design.

Polo-like kinase 2 promotes microglial activation via regulation of the HSP90α/IKKß pathway.

Polo-like kinase 2 (PLK2) is a serine/threonine protein kinase associated with the regulation of synaptic plasticity and centriole duplication. We identify PLK2 as a crucial early-response gene in lipopolysaccharide (LPS)-stimulated microglial cells. Knockdown or inhibition of PLK2 remarkably attenuates LPS-induced expression of proinflammatory factors in microglial cells by suppressing the inhibitor of nuclear factor kappa B kinase subunit beta (IKKß)-nuclear factor (NF)-κB signaling pathway. We identify heat shock protein 90 alpha (HSP90α), a regulator of IKKß activity, as a novel PLK2 substrate. Knockdown or pharmacological inhibition of HSP90α abolishes PLK2-mediated activation of NF-κB transcriptional activity and microglial inflammatory activation. Furthermore, phosphoproteomic analysis pinpoints Ser252 and Ser263 on HSP90α as novel phosphorylation targets of PLK2. Lastly, conditional knockout of PLK2 in microglial cells dramatically ameliorates neuroinflammation and subsequent dopaminergic neuron loss in an intracranial LPS-induced mouse Parkinson's disease (PD) model. The present study reveals that PLK2 promotes microglial activation through the phosphorylation of HSP90α and subsequent activation of the IKKß-NF-κB signaling pathway.

Bicanalicular stent versus mono-canalicular stent for post-oncological lacrimal duct reconstruction: A retrospective cohort study.

BACKGROUND: Bicanalicular and mono-canalicular stent intubations were developed for post-oncological lacrimal duct reconstruction; however, comparative analysis between the two surgical modalities is lacking. This study aimed to compare the surgical outcomes between the two types of stents at a single institution. MATERIALS AND METHODS: Briefly, 75 eyes of 75 patients who underwent lacrimal reconstruction combined with lacrimal stent intubation were enrolled in this study and were divided into bicanalicular stent intubation and mono-canalicular stent intubation groups. The clinical characteristics, follow-up, and prognosis were compared between the two groups. RESULTS: Bicanalicular and mono-canalicular stent intubations were performed in 36 eyes (36 patients; Group A) and 39 eyes (39 patients; Group B), respectively. The difference in stent duration between Groups A and B was statistically significant. Three eyes in Group A and one eye in Group B experienced postoperative stent prolapse. Two eyes in Group B showed punctum stenosis and one eye had punctal ectropion. Seven eyes in Group A had canalicular slitting. There were no statistically significant differences in the mean preoperative Munk scores between the two groups. There were no statistically significant differences in the mean Munk scores and mean VAS scores at 1 week postoperatively, before stent removal, and 3 months after stent removal between the two groups. CONCLUSION: Bicanalicular and mono-canalicular stent intubations were equally effective in ensuring lacrimal duct patency and in preventing postoperative epiphora. Appropriate cases and stent selection can reduce the incidence of postoperative complications.

Plant-derived biomass-based hydrogels for biomedical applications.

Hydrogels made of plant-derived biomass have gained popularity in biomedical applications because they are frequently affordable, readily available, and biocompatible. Finding the perfect plant-derived biomass-based hydrogels for biomedicine that can replicate essential characteristics of human tissues in regard to structure, function, and performance has proved to be difficult. In this review, we summarize some of the major contributions made to this topic, covering basic ideas and different biomass-based hydrogels made of cellulose, hemicellulose, and lignin. Also included is an in-depth discussion regarding the biosafety and toxicity assessments of biomass-based hydrogels. Finally, this review also highlights important scientific debates and major obstacles regarding biomass-based hydrogels for biomedical applications.

Association of metabolically healthy obesity with risk of heart failure and left ventricular dysfunction among older adults.

BACKGROUND: Obesity is major cause of heart failure (HF), but it is related with a better prognosis among the elderly. Therefore, we aimed to examine whether metabolically healthy obesity (MHO) in late life increases HF risk and is reflected in impaired left ventricular (LV) function. METHODS: The participants were grouped into four metabolic phenotypes based on obesity and metabolic status: metabolically healthy non-obesity (MHN), MHO, metabolically unhealthy non-obesity (MUN), metabolically unhealthy obesity (MUO). Association of metabolic phenotypes with LV function was evaluated using multiple linear regression models. And association between metabolic phenotypes and risk of HF was assessed using multivariable logistic regression models. In addition, we validated the association of metabolic phenotypes and HF risk in a separate longitudinal cohort. RESULTS: In the primary cohort of 6335 participant, there were 434 participants diagnosed with HF. Compared to MHN participants, the risk of HF was higher among older individuals with MUN (OR = 1.51 [95% CI: 1.14-1.99]) and MUO (OR = 2.01 [95% CI: 1.39-2.91]), but not older individuals with MHO (OR = 0.86 [95% CI: 0.30-2.43). Regarding to LV function, worse LV diastolic function was noted among MUN and MUO individuals rather than MHO individuals. Older adults with MHO were also not associated with risk of HF in the validation cohort. CONCLUSION: Among older individuals, the metabolic health status might modify the association of obesity with risk of HF and LV diastolic dysfunction. Worse LV diastolic function and higher risk of HF were just noted in individuals with MUO, but not in those with MHO.

Regulation of the NF-κB/NLRP3 signalling pathway by Shenghui Yizhi decoction reduces neuroinflammation in mice with Alzheimer's disease.

BACKGROUND: Shenghui Yizhi Decoction (SHYZD) has exhibited the capacity to enhance cognitive function and learning abilities in individuals diagnosed with Alzheimer's disease (AD) while ameliorating pre-existing neuroinflammation. Nevertheless, the precise mechanism underlying its therapeutic effects on AD remains to be elucidated. METHODS: Twenty-four male SAMP8 mice were randomly divided into three groups, and eight male SAMR1 mice were used as a blank control, to examine their learning and spatial memory abilities. The expression of amyloid ß1-42 (Aß1-42) was detected by immunohistochemical staining of hippocampal tissue. ELISA was used to detect the interleukin-1ß (IL-1ß), interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) expressions. Real time PCR was used to detect NOD-like receptor thermal protein domain associated protein 3 (NLRP3), cysteine protease-1 (Caspase-1), and IL-1ß mRNA expression. Western blot was used to detect nuclear factor kappa-B (NF-κB), inhibitor of NF-κB α (IκBα), IκB kinase α (IKKα), NLRP3, Caspase-1, and IL-1ß protein expression. RESULTS: In this study, SAMP8 mice, employed as an AD model, displayed markedly diminished abilities in terms of spatial localization, navigation, and spatial exploration when compared to the blank control group. Additionally, there was a substantial upregulation of Aß1-42 expression in the hippocampus of these mice, along with a significant increase in the levels of inflammation-associated factors, including IL-1ß, IL-6, TNF-α, NLRP3, Caspase-1, as well as the NF-κB pathway-related proteins, namely, NF-κB, IκBα, and IKKα. Moreover, after treatment with positive drugs (donepezil hydrochloride) and SHYZD, the learning abilities of the mice exhibited significant improvements. Furthermore, the hallmark AD protein Aß1-42, inflammatory factors, and NF-κB/NLRP3 signalling pathway proteins were significantly reduced. These findings collectively suggest that SHYZD exerts a therapeutic effect on AD. CONCLUSION: In summary, the specific molecular mechanisms through which SHYZD alleviates AD and the potential role for SHYZD in the NF-κB/NLRP3 signalling pathway are identified in this study.

Root endodermal suberization induced by nitrate stress regulate apoplastic pathway rather than nitrate uptake in tobacco (Nicotiana tabacum L.).

Nitrogen levels and distribution in the rhizosphere strongly regulate the root architecture. Nitrate is an essential nutrient and an important signaling molecule for plant growth and development. Hydroponic experiments were conducted to investigate the differences in endodermal suberization in tobacco (Nicotiana tabacum L.) roots at three nitrate levels. Nitrogen accumulation was detected in the roots, shoots, and xylem sap. Nitrate influx on the root surface was also measured using the non-invasive self-referencing microsensor technique (SRMT). RNA-Seq analysis was performed to identify the genes related to endodermal suberization, nitrate transport, and endogenous abscisic acid (ABA) biosynthesis. The results showed that root length, root-shoot ratio, nitrate influx on the root surface, and NiA and NRT2.4 genes were regulated to maintain the nitrogen nutrient supply in tobacco under low nitrate conditions. Low nitrate levels enhanced root endodermal suberization and hence reduced the apoplastic transport pathway, and genes from the KCS, FAR, PAS2, and CYP86 families were upregulated. The results of exogenous fluridone, an ABA biosynthesis inhibitor, indicated that suberization of the tobacco root endodermis had no relevance to radial nitrate transport and accumulation. However, ABA enhances suberization, relating to ABA biosynthesis genes in the CCD family and degradation gene ABA8ox1.

A review of airborne micro- and nano-plastics: Sampling methods, analytical techniques, and exposure risks.

Atmospheric Micro- and nano-plastics (MNPs) can be easily inhaled and ingested by humans and have become a global health concern. With the development of instruments and techniques, an increasing number of sampling and analytical methods have been applied to study airborne MNPs. Active samplers and passive collectors are used to collect suspended aerosols and atmospheric depositions. Microscopes and scanning electron microscopy (SEM) have been used to physically identify the MNPs, while Fourier transform infrared (FTIR), Raman spectroscopy, and Pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) are used to identify the polymer compositions of the MNPs. However, the diversity of methods and strategies has greatly limited our ability to compare results and assess exposure risks. In this review, we extracted data from PubMed, Embase, and Scopus from 2018 to 2024 that reported sampling methods, analytical techniques, and abundance/deposition of airborne MNPs. Through a systematic review of the included 140 articles, we emphasized the advantages and limitations of different methods for collecting and analyzing airborne MNPs. In addition, we provided an in-depth analysis of the performance of specific methods across different airborne environments. Furthermore, the current knowledge regarding the abundance, deposition, exposure risks of airborne MNPs, and exposure risk assessment models has been discussed. Finally, we provide concrete recommendations for standardization of methods. This review identified knowledge gaps and recommended future research directions for exposure assessment of airborne MNPs.

Vanillic Acid Protects PC12 Cells from Corticosterone-Induced Neurotoxicity via Regulating Immune and Metabolic Dysregulation Based on Computational Metabolomics.

Vanillic acid is widely used in the food industry and exhibits an excellent neuroprotective effect. Nevertheless, the mechanisms underlying them are largely unexplored, especially the interactions between the neuroprotection effects of vanillic acid and inflammation-immunity-metabolism. A cell metabolomics-based mathematics algorithm was reported to interpret the potential mechanism of vanillic acid on corticosterone-induced PC12 cells by regulating immune and metabolic dysregulation. Our results showed that vanillic acid markedly inhibited the level of inflammatory factors in corticosterone-induced PC12 cells. Cell metabolomics results suggested that vanillic acid regulated the abnormality of corticosterone-induced PC12 cell metabolic profiles and markedly regulated 11 differential metabolites. Our designed scoring model base entropy weight algorithm showed that the core targets (IL2RB, IFNA13, etc.) and metabolites (lactate, ethanolamine, etc.) regulate the immunity-metabolism of vanillic acid. Furthermore, we demonstrated that vanillic acid inhibited IL2RB expression and modulated the related pathway, JAK1/STAT3 signaling. The JAK inhibitor ABT-494 was further applied to validate the effect of vanillic acid on the JAK/STAT pathway. Results indicate that vanillic acid regulates the abnormal interactions of inflammation-immunity-metabolism by repressing the IL2RB-JAK1-STAT3 pathway. Methodologically, this study contributes to the decoding of vanillic acid's antidepressive effect from the metabolism perspective combined with computer algorithms and mathematics models.

Primary Sjogren's Syndrome Associated with Lung Adenocarcinoma: Probing the Potential Common Pathogenic Mechanisms and Experimental Verification.

This study aimed to probe the potential common pathogenic mechanisms linking primary Sjogren's syndrome (pSS) and lung adenocarcinoma (LUAD) through bioinformatics analysis and experimental verification. The relevant genes associated with pSS and LUAD were retrieved from the Gene Expression Omnibus (GEO) database and Genecard database. Subsequently, differentially expressed genes (DEGs) associated with pSS and LUAD were screened as pSS-LUAD-DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to elucidate the significant biological functions of pSS-LUAD-DEGs. Core targets were identified by constructing the protein-protein interaction (PPI) network, further assessing hub gene diagnostic accuracy through Receiver Operating Characteristic (ROC) curve analyses. In this study, NOD/Ltj mice served as pSS animal models and were stimulated with particulate matter 2.5 (PM2.5) to generate an inflammatory reaction. Quantitative real-time polymerase chain reaction (qPCR), enzyme-linked immunosorbent assay (ELISA), and western blotting were employed for relevant molecular biology experiment verification. The results revealed through KEGG and GO enrichment analyses indicate that inflammation plays a critical role in linking pSS and LUAD. IL6, CCNA2, JAK2, IL1B, ASPM, CCNB2, NUSAP1, and CEP55 were determined as key targets of pSS-LUAD. BALB/c mice and NOD/Ltj mice exhibited enhanced expression of inflammatory cytokines IL-6 and IL-1ß in lung tissues following 21 days of stimulation with PM2.5, activating the JAK2/STAT3 signaling pathway and up-regulating the expression of tumor-associated genes CCNA2, CCNB2, and CEP55, with NOD/Ltj mice exhibiting more pronounced changes than BALB/c mice. This protocol demonstrates that carcinogenesis induced by the pulmonary inflammatory microenvironment may be a key reason for the high incidence of LUAD in pSS patients. Additionally, blocking-related mechanisms may help prevent the occurrence of LUAD in pSS patients.

Breakthroughs in AI and multi-omics for cancer drug discovery: A review.

Cancer is one of the biggest medical challenges we face today. It is characterized by abnormal, uncontrolled growth of cells that can spread to different parts of the body. Cancer is extremely complex, with genetic variations and the ability to adapt and evolve. This means we must continuously pursue innovative approaches to developing new cancer drugs. While traditional drug discovery methods have led to important breakthroughs, they also have significant limitations that make it difficult to efficiently create new, cost-effective cancer therapies. Integrating computational tools into the cancer drug discovery process is a major step forward. By harnessing computing power, we can overcome some of the inherent barriers of traditional methods. This review examines the range of computational techniques now being used, such as molecular docking, QSAR models, virtual screening, and pharmacophore modeling. It looks at recent advances in areas like machine learning and molecular simulations. The review also discusses the current challenges with these technologies and envisions future directions, underscoring how transformative these computational tools can be for creating targeted, new cancer treatments.

Comprehensive Analysis of Angiogenesis and Ferroptosis Genes for Predicting the Survival Outcome and Immunotherapy Response of Hepatocellular Carcinoma.

Background: Angiogenesis and ferroptosis are both linked to hepatocellular carcinoma (HCC) development, recurrence, and medication resistance. As a result, a thorough examination of the link between genes associated with angiogenesis and ferroptosis and immunotherapy efficacy is required to improve the dismal prognosis of HCC patients. Methods: The molecular subtypes were found using a non-negative matrix factorization technique (NMF) based on the genes associated with angiogenesis and ferroptosis. Based on the differentially expressed genes (DEGs) screed between different molecular subtypes, an angiogenesis and ferroptosis-related prognostic stratification model was built using LASSO-COX regression, random forest technique, and extreme gradient boosting (XGBoost), which was further validated in the ICGC and GSE14520 databases. The impact of this model on tumor microenvironment (TME) and immunotherapy sensitivity was also investigated. The expression levels of candidate genes were detected and validated by Real-Time PCR and immunohistochemistry between liver cancer tissues and adjacent non-tumor liver tissues. Results: Both angiogenesis and ferroptosis-related genes can significantly divide HCC patients into two subgroups with different survival outcomes, mutation profiles, and immune microenvironments. We screened six core genes (SLC10A1, PAEP, DPYSL4, MSC, NQO1, and CD24) for the construction of prognostic models by three machine learning methods after intersecting DEGs between angiogenesis and ferroptosis-related subgroups. In both the TCGA, ICGC, and GSE14520 datasets, the model exhibits high prediction efficiency based on the analysis of KM survival curves and ROC curves. Immunomodulatory genes analysis suggested that the model could be used to predict which patients are most likely to benefit from immunotherapy. Furthermore, the transcriptional expression levels of SLC10A1 in the validation experiment matched the outcomes derived from public datasets. Conclusions: We identified a new angiogenesis and ferroptosis-related signature that might offer the molecular characteristic information needed for an efficient prognostic assessment and perhaps tailored treatment for HCC patients.