Targeting senescent cells in aging and COVID-19: from cellular mechanisms to therapeutic opportunities.

The COVID-19 pandemic has caused a global health crisis and significant social economic burden. While most individuals experience mild or non-specific symptoms, elderly individuals are at a higher risk of developing severe symptoms and life-threatening complications. Exploring the key factors associated with clinical severity highlights that key characteristics of aging, such as cellular senescence, immune dysregulation, metabolic alterations, and impaired regenerative potential, contribute to disruption of tissue homeostasis of the lung and worse clinical outcome. Senolytic and senomorphic drugs, which are anti-aging treatments designed to eliminate senescent cells or decrease the associated phenotypes, have shown promise in alleviating age-related dysfunctions and offer a novel approach to treating diseases that share certain aspects of underlying mechanisms with aging, including COVID-19. This review summarizes the current understanding of aging in COVID-19 progression, and highlights recent findings on anti-aging drugs that could be repurposed for COVID-19 treatment to complement existing therapies.

Chemically programmed metabolism drives a superior cell fitness for cartilage regeneration.

The rapid advancement of cell therapies underscores the importance of understanding fundamental cellular attributes. Among these, cell fitness-how transplanted cells adapt to new microenvironments and maintain functional stability in vivo-is crucial. This study identifies a chemical compound, FPH2, that enhances the fitness of human chondrocytes and the repair of articular cartilage, which is typically nonregenerative. Through drug screening, FPH2 was shown to broadly improve cell performance, especially in maintaining chondrocyte phenotype and enhancing migration. Single-cell transcriptomics indicated that FPH2 induced a super-fit cell state. The mechanism primarily involves the inhibition of carnitine palmitoyl transferase I and the optimization of metabolic homeostasis. In animal models, FPH2-treated human chondrocytes substantially improved cartilage regeneration, demonstrating well-integrated tissue interfaces in rats. In addition, an acellular FPH2-loaded hydrogel proved effective in preventing the onset of osteoarthritis. This research provides a viable and safe method to enhance chondrocyte fitness, offering insights into the self-regulatory mechanisms of cell fitness.

A novel "turn-on" NIR fluorescent probe based on benzothianone for the detection of palladium species and its application in cell and zebrafish.

The development of an efficient palladium probe holds significant application value, considering the detrimental impact of palladium contaminants on human health. Thus, it is critical to create a sensitive detection method. To this end, a fluorescent probe TM-TPA-Pd based on benzothianone structure was designed, using allyl carbonate as the Pd0 recognition unit. TM-TPA-Pd exhibited high sensitivity (1.4 eq), selectivity, near-infrared (NIR) fluorescence (798 nm), and low detection limit (0.46 µM) for Pd0 with a rapid "turn-on" fluorescence signal (5 min). Furthermore, TM-TPA-Pd has extremely low cytotoxicity and has been successfully applied to detecting cells and zebrafish, which has great potential for palladium detection in biological systems.

Genetically predicted lipid traits mediate the association between folic acid and atherosclerosis.

Atherosclerosis (AS) is one of the most common causes of death from cardiovascular disease, and low folic acid (FA) levels have been reported to be strongly associated with an increased risk of AS. We aimed to obtain causal estimates of the association between FA and AS and to quantify the mediating role of known modifiable risk factors. Based on the largest genome-wide association study (GWAS) from the IEU Open GWAS Project for all human studies, we conducted a two-sample Mendelian randomization (MR) study of genetically predicted FA and AS. A two-step MR design was then used to assess the causal mediating effect of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) on the relationship between FA and AS. This MR analysis showed that genetically determined FA levels [IVW: Odds Ratio (OR) = 0.623, 95% CI 0.421-0.924, P = 0.018] were associated with a reduced risk of AS. Inverse variance weighted (IVW) MR analysis also showed that genetically predicted FA was positively correlated with HDL-C levels (OR = 1.358, 95% CI 1.029-1.792, P = 0.031) and negatively correlated with LDL-C (OR = 0.956, 95% CI 0.920-0.994, P = 0.023) and TG levels (OR = 0.929, 95% CI 0.886-0.974, P = 0.003). LDL-C, HDL-C, and TG mediate 3.00%, 6.80%, and 4.40%, respectively, of the total impact of FA on AS. The combined effect of these three factors accounts for 13.04% of the total effect. Sensitivity analysis verifies the stability and reliability of the results. These results support a potential causal protective effect of FA on AS, with considerable mediation through many modifiable risk factors. Thus, interventions on levels of LDL-C, HDL-C, and TG have the potential to substantially reduce the burden of AS caused by low FA.

A Multibranch Neural Network for Drug-Target Affinity Prediction Using Similarity Information.

Predicting drug-target affinity (DTA) is beneficial for accelerating drug discovery. In recent years, graph structure-based deep learning models have garnered significant attention in this field. However, these models typically handle drug or target protein in isolation and only extract the molecular structure information on the drug or protein itself. To address this limitation, existing network-based models represent drug-target interactions or affinities as a knowledge graph to capture the interaction information. In this study, we propose a novel solution. Specifically, we introduce drug similarity information and protein similarity information into the field of DTA prediction. Moreover, we propose a network framework that autonomously extracts similarity information, avoiding reliance on knowledge graphs. Based on this framework, we design a multibranch neural network called GASI-DTA. This network integrates similarity information, sequence information, and molecular structure information. Comprehensive experimental results conducted on two benchmark data sets and three cold-start scenarios demonstrate that our model outperforms state-of-the-art graph structure-based methods in nearly all metrics. Furthermore, it exhibits significant advantages over existing network-based models, outperforming the best of them in the majority of metrics. Our study's code and data are openly accessible at http://github.com/XiaoLin-Yang-S/GASI-DTA.

Predictive value of isolated very low QRS voltage in tilt-table test for neurally mediated syncope.

Objective: The cause of syncope is generally determined based on clinical manifestations. There has been little discussion about the value of electrocardiograms for diagnosing neurally mediated syncope. The aim of this study was to test the predictive value of the isolated very low QRS voltage in tilt-table testing for suspected neurally mediated syncope in a Chinese population. Methods: This retrospective study enrolled patients with suspected neurally mediated syncope. Tilt-table testing was a part of the diagnostic examination. Each patient underwent echocardiography and electrocardiogram. isolated very low QRS voltage referred to a voltage of ⩽0.3 mV for the QRS complex in an isolated frontal lead or ⩽0.7 mV for the QRS complex in an isolated precordial lead. Results: In total, 157 patients were included in the tilt-table testing positive group, and 242 patients were included in the tilt-table testing negative group. Compared with the testing negative group, the testing positive group had more patients with isolated very low QRS voltage in the frontal leads (p < 0.001). Moreover, for patients with isolated very low QRS voltage in the precordial leads, no significant difference was noted between the testing positive group and testing negative group (p = 0.289). Isolated very low QRS voltage in the frontal leads demonstrated 84.08% sensitivity and 74.38% specificity for a positive tilt-table testing response. The area under the curve of isolated very low QRS voltage for a positive tilt-table testing response in frontal leads was 0.806 (p < 0.0001). Conclusion: In patients with suspected neurally mediated syncope, isolated very low QRS voltage in the frontal leads is a parameter that can predict a positive tilt-table testing response. The presence of isolated very low QRS voltage in frontal leads can serve as a parameter for evaluating syncope patients.

A Comparison Analysis of Quality and Metabolic Compounds in Lilies with Different Drying Treatments.

The present study aimed to investigate the variations in the nutritional composition, antioxidant capacity, and metabolite profile of lilies subjected to different drying treatments, including vacuum freeze drying (VFD), hot air drying (HAD), vacuum drying (VD), and infrared drying (ID). The results show that VFD provided better preservation of the original coloration and displayed the highest levels of total amino acid content, total phenolic content, total flavonoid content, and polysaccharide and alkaloid content. Our results reveal that VFD treatment can be employed to obtain high-quality lilies with desirable appearance characteristics and nutrient compositions. Metabolomics analysis identified a total of 464 metabolites from various dried lilies. Differential metabolite screening found 150 differential metabolites across all pairwise comparisons. Hierarchical clustering analysis (HCA) indicated that lilies subjected to VFD treatment exhibited a higher abundance of steroids, saponin, flavonoids, and phenolic glycoside, whereas those subjected to HAD, VD, or ID treatments showed relatively elevated levels of specific amino acids or derivatives. This study elucidates the significant impact of various drying treatments on the quality and metabolic profile of lilies, thereby providing valuable insights for enhancing the nutritional quality of processed lilies.

Multi-Scale Feature and Multi-Channel Selection toward Parkinson's Disease Diagnosis with EEG.

OBJECTIVE: Motivated by Health Care 4.0, this study aims to reducing the dimensionality of traditional EEG features based on manual extracted features, including statistical features in the time and frequency domains. METHODS: A total of 22 multi-scale features were extracted from the UNM and Iowa datasets using a 4th order Butterworth filter and wavelet packet transform. Based on single-channel validation, 29 channels with the highest R2 scores were selected from a pool of 59 common channels. The proposed channel selection scheme was validated on the UNM dataset and tested on the Iowa dataset to compare its generalizability against models trained without channel selection. RESULTS: The experimental results demonstrate that the proposed model achieves an optimal classification accuracy of 100%. Additionally, the generalization capability of the channel selection method is validated through out-of-sample testing based on the Iowa dataset Conclusions: Using single-channel validation, we proposed a channel selection scheme based on traditional statistical features, resulting in a selection of 29 channels. This scheme significantly reduced the dimensionality of EEG feature vectors related to Parkinson's disease by 50%. Remarkably, this approach demonstrated considerable classification performance on both the UNM and Iowa datasets. For the closed-eye state, the highest classification accuracy achieved was 100%, while for the open-eye state, the highest accuracy reached 93.75%.

Association of CD8+TILs co-expressing granzyme A and interferon-γ with colon cancer cells in the tumor microenvironment.

CD8+T cells secreting granzyme A (GZMA) can induce pyroptosis in tumor cells by effectively cleaving gasdermin B (GSDMB), which is stimulated by interferon-γ (IFN-γ). However, the interaction between GZMA-expressing CD8+T cells and GSDMB-expressing tumor cells in colon cancer remains poorly understood. Our research employed multi-color immunohistochemistry (mIHC) staining and integrated clinical data to explore the spatial distribution and clinical relevance of GZMA- and IFN-γ-expressing CD8+ tumor-infiltrating lymphocytes (TILs), as well as GSDMB-expressing CK+ cells, within the tumor microenvironment (TME) of human colon cancer samples. Additionally, we utilizing single-cell RNA sequencing (scRNA-seq) data to examine the functional dynamics and interactions among these cell populations. scRNA-seq analysis of colorectal cancer (CRC) tissues revealed that CD8+TILs co-expressed GZMA and IFN-γ, but not other cell types. Our mIHC staining results indicated that a significant reduction in the infiltration of GZMA+IFN-γ+CD8+TILs in colon cancer patients (P < 0.01). Functional analysis results indicated that GZMA+IFN-γ+CD8+TILs demonstrated enhanced activation and effector functions compared to other CD8+TIL subsets. Furthermore, GSDMB-expressing CK+ cells exhibited augmented immunogenicity. Correlation analysis highlighted a positive association between GSDMB+CK+ cells and GZMA+IFN-γ+CD8+TILs (r = 0.221, P = 0.033). Analysis of cell-cell interactions further showed that these interactions were mediated by IFN-γ and transforming growth factor-ß (TGF-ß), the co-stimulatory molecule ICOS, and immune checkpoint molecules TIGIT and TIM-3. These findings suggested that GZMA+IFN-γ+CD8+TILs modulating GSDMB-expressing tumor cells, significantly impacted the immune microenvironment and patients' prognosis in colon cancer. By elucidating these mechanisms, our present study aims to provide novel insights for the advancement of immunotherapeutic strategies in colon cancer.

Diagnostic Performance of Noninvasive Coronary Computed Tomography Angiography-Derived FFR for Coronary Lesion-Specific Ischemia Based on Deep Learning Analysis.

Background: The noninvasive computed tomography angiography-derived fractional flow reserve (CT-FFR) can be used to diagnose coronary ischemia. With advancements in associated software, the diagnostic capability of CT-FFR may have evolved. This study evaluates the effectiveness of a novel deep learning-based software in predicting coronary ischemia through CT-FFR. Methods: In this prospective study, 138 subjects with suspected or confirmed coronary artery disease were assessed. Following indication of 30%-90% stenosis on coronary computed tomography (CT) angiography, participants underwent invasive coronary angiography and fractional flow reserve (FFR) measurement. The diagnostic performance of the CT-FFR was determined using the FFR as the reference standard. Results: With a threshold of 0.80, the CT-FFR displayed an impressive diagnostic accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) of 97.1%, 96.2%, 97.7%, 0.98, 96.2%, and 97.7%, respectively. At a 0.75 threshold, the CT-FFR showed a diagnostic accuracy, sensitivity, specificity, AUC, PPV, and NPV of 84.1%, 78.8%, 85.7%, 0.95, 63.4%, and 92.8%, respectively. The Bland-Altman analysis revealed a direct correlation between the CT-FFR and FFR (p < 0.001), without systematic differences (p = 0.085). Conclusions: The CT-FFR, empowered by novel deep learning software, demonstrates a strong correlation with the FFR, offering high clinical diagnostic accuracy for coronary ischemia. The results underline the potential of modern computational approaches in enhancing noninvasive coronary assessment.

Diagnostic performance of the quantitative flow ratio and CT-FFR for coronary lesion-specific ischemia.

Fractional flow reserve (FFR) has become the gold standard for evaluating coronary lesion-specific ischemia. However, FFR is an invasive method that may cause possible complications in the coronary artery and requires expensive equipment, which limits its use. Promising noninvasive diagnostic methods, such as computed tomography angiography-derived FFR (CT-FFR) and the quantitative flow ratio (QFR), have been proposed. In this study, we evaluated the diagnostic performance of the QFR and CT-FFR in predicting coronary lesion-specific ischemia, with the FFR serving as the reference standard. Patients with suspected or known coronary artery disease who underwent coronary CT angiography revealing 30-90% diameter stenosis in the main coronary artery (≥ 2.0 mm reference diameter) were enrolled. The FFR was measured during invasive coronary angiography (within 15 days after coronary CT angiography). An FFR ≤ 0.8 was the reference standard for coronary lesion-specific ischemia. A total of 103 vessels from 92 consecutive patients (aged 59.8 ± 9.2 years; 60.9% were men) were evaluated. The diagnostic performance of a QFR ≤ 0.80 for predicting coronary lesion-specific ischemia demonstrated good diagnostic accuracy, sensitivity, and specificity (92.2%, 87.2%, and 96.4%, respectively), with an area under the receiver operating characteristic curve (AUC) of 0.987 (P < 0.0001). The diagnostic performance of a CT-FFR ≤ 0.80 for predicting coronary lesion-specific ischemia also demonstrated good diagnostic accuracy, sensitivity, and specificity (96.1%, 95.7%, and 96.4%, respectively), with an AUC of 0.967 (P < 0.0001). However, there was no significant difference in the AUC between a QFR ≤ 0.80 and a CT-FFR ≤ 0.80 for predicting coronary lesion-specific ischemia (P = 0.319). There was an excellent correlation between the QFR and FFR (r = 0.856, P < 0.0001). The CT-FFR and FFR also showed a good direct correlation (r = 0.816, P < 0.0001). The QFR and CT-FFR are strongly correlated with the FFR and can provide excellent clinical diagnostic performance for coronary lesion-specific ischemia detection.

Low loss, wideband, and high extinction ratio TM polarizer based on subwavelength gratings.

We propose a low loss, wideband silicon transverse magnetic (TM) polarizer with high polarization extinction ratio and low reflection based on subwavelength grating. By arranging and optimizing a mutually perpendicular subwavelength grating with different duty cycles as the core and cladding, efficient waveguiding and radiation can be achieved for the TM and transverse electric (TE) injection, respectively. In simulation, the proposed TM polarizer has a footprint of 40µm×16.68µm, an insertion loss <0.7d B, a polarization extinction ratio ≥20d B, and an unwanted TE reflection <-17.4d B in the wavelength range of 1230-1700 nm. Moreover, the fabrication tolerance of the proposed device is also investigated.

A retrospective case-control study on the effectiveness of preoperative diffusion tensor imaging for mitigating nerve injury in extreme lateral interbody fusion surgery.

BACKGROUND CONTEXT: Extreme Lateral Interbody Fusion (XLIF) has been established as an effective treatment for degenerative disorders of the lumbar spine. Nevertheless, there is a potential risk of lumbar plexus damage associated with XLIF, especially during surgeries at the L4-5 segment. Diffusion Tensor Imaging (DTI) evaluates the directional diffusion of water molecules in tissue, providing a more intricate depiction of internal tissue microstructure compared to conventional MRI techniques. The capability of DTI sequences to elucidate the 3-dimensional interplay between lumbar nerve pathways and adjacent musculoskeletal structures, potentially reducing the incidence of nerve injury complications related to XLIF, remains to be established. PURPOSE: This study evaluates the effectiveness of preoperative Diffusion Tensor Imaging (DTI) in reducing neurological complications after Extreme Lateral Interbody Fusion (XLIF) surgeries at the L4-5 level, focusing on the interaction between lumbar nerves and the psoas major muscle. STUDY DESIGN: Retrospective case-control study. PATIENT SAMPLE: The study included 128 patients undergoing XLIF surgery for degenerative disorders at the L4-5 segment: 68 in the traditional group and 62 in the DTI group. OUTCOME MEASURES: The study assessed Visual Analogue Scale (VAS) and Oswestry Disability Index (ODI) scores, along with complication rates. It also documented psoas major muscle morphology and its correlation with nerve pathways. METHODS: A retrospective analysis of 128 patients undergoing XLIF surgery for degenerative disorders at the L4-5 segment between February 2020 and August 2022 was conducted. The cohort was divided into a traditional group (68 patients) receiving presurgery MRI scans to identify surgical entry points at the intervertebral space midpoint (Zones II-III junction) and a DTI group (62 patients) who additionally underwent preoperative DTI to customize entry points. The study evaluated VAS and ODI scores, complication rates, psoas major muscle morphology, and its interaction with nerve pathways. RESULTS: The traditional group uniformly chose the Zone II-III junction for entry. In contrast, the DTI group's entry points varied. Postoperative follow-up revealed significant improvements in VAS and ODI scores in both groups. However, the DTI group experienced fewer immediate postoperative complications such as thigh pain, numbness, and motor disturbances. The study also noted a ventral shift in nerve positioning in patients with elevated psoas muscles. CONCLUSIONS: Preoperative DTI effectively maps the relationship between the psoas major muscle and lumbar nerves. Tailoring surgical entry points based on DTI results significantly reduces the risk of nerve damage in XLIF surgeries. The study underscores the importance of recognizing variability in lumbar nerve pathways due to differing psoas muscle morphologies, highlighting a higher risk of nerve injury in patients with elevated psoas muscles during XLIF procedures.

Ferredoxin 1: a gatekeeper in halting lung adenocarcinoma progression through activation of the GPRIN2 signaling pathway.

BACKGROUND: Lung adenocarcinoma (LUAD) is a highly lethal form of lung cancer. Despite advancements in treatments, managing LUAD is still challenging due to its aggressive behavior. Recent studies indicate that various molecular pathways, including the dysregulation of ferredoxin 1 (FDX1), play roles in LUAD progression. FDX1, a crucial protein in cellular redox reactions and energy metabolism, has been linked to several cancers. However, its exact role in the development of LUAD is not yet fully understood. METHODS: We investigated the role of ferredoxin 1 (FDX1) in LUAD progression through analysis of its expression in LUAD tissues and its impact on patient survival. Functional assays were performed to assess the effects of FDX1 overexpression on LUAD cell proliferation, migration, and invasion. A xenograft model was employed to evaluate the tumorigenesis potential of LUAD cells with FDX1 overexpression. Mechanistic insights into FDX1 regulation were gained through depletion experiments targeting the G protein-regulated inducer of neurite outgrowth 2 (GPRIN2)/PI3K signaling pathway. RESULTS: FDX1 expression was down-regulated in LUAD tissues, correlating with shorter patient survival. Overexpression of FDX1 suppressed LUAD cell proliferation, migration, and invasion in vitro, and inhibited tumorigenesis in vivo. Mechanistically, the GPRIN2/PI3K signaling pathway was implicated in FDX1 regulation, as depletion of GPRIN2 reversed the effects of FDX1 overexpression on cellular functions. CONCLUSIONS: Our findings highlight FDX1 as a potential tumor suppressor in LUAD, acting through modulation of the GPRIN2/PI3K signaling pathway. These results suggest FDX1 as a promising therapeutic target for LUAD treatment, warranting further investigation into its clinical relevance.

Uncovering Gender-Specific and Cross-Gender Features in Mandarin Deception: An Acoustic and Electroglottographic Approach.

PURPOSE: This study aimed to investigate the acoustic and electroglottographic (EGG) profiles of Mandarin deception, including global characteristics and the influence of gender. METHOD: Thirty-six Mandarin speakers participated in an interactive interview game in which they provided both deceptive and truthful answers to 14 biographical questions. Acoustic and EGG signals of the participants' responses were simultaneously recorded; 20 acoustic and 14 EGG features were analyzed using binary logistic regression models. RESULTS: Increases in fundamental frequency (F0) mean, intensity mean, first formant (F1), fifth formant (F5), contact quotient (CQ), decontacting-time quotient (DTQ), and contact index (CI) as well as decreases in jitter, shimmer, harmonics-to-noise ratio (HNR), and fourth formant (F4) were significantly correlated with global deception. Cross-gender features included increases in intensity mean and F5 and decreases in jitter, HNR, and F4, whereas gender-specific features encompassed increases in F0 mean, shimmer, F1, third formant, and DTQ, as well as decreases in F0 maximum and CQ for female deception, and increases in CQ and CI and decreases in shimmer for male deception. CONCLUSIONS: The results suggest that Mandarin deception could be tied to underlying pragmatic functions, emotional arousal, decreased glottal contact skewness, and more pressed phonation. Disparities in gender-specific features lend support to differences in the use of pragmatics, levels of deception-induced emotional arousal, skewness of glottal contact patterns, and phonation types.

Low blood flow ratio is associated with hemorrhagic transformation secondary to mechanical thrombectomy in patients with acute ischemic stroke.

BACKGROUND AND PURPOSE: A significant decrease of cerebral blood flow (CBF) is a risk factor for hemorrhagic transformation (HT) in acute ischemic stroke (AIS). This study aimed to ascertain whether the ratio of different CBF thresholds derived from computed tomography perfusion (CTP) is an independent risk factor for HT after mechanical thrombectomy (MT). METHODS: A retrospective single center cohort study was conducted on patients with AIS undergoing MT at the First Affiliated Hospital of Wenzhou Medical University from August 2018 to December 2023. The perfusion parameters before thrombectomy were obtained according to CTP automatic processing software. The low blood flow ratio (LFR) was defined as the ratio of brain volume with relative CBF <20 % over volume with relative CBF <30 %. HT was evaluated on the follow-up CT images. Binary logistic regression was used to analyze the correlation between parameters that differ between the two groups with regards to HT occurrence. The predictive efficacy was assessed utilizing the receiver operating characteristic curve. RESULTS: In total, 243 patients met the inclusion criteria. During the follow-up, 46.5 % of the patients (113/243) developed HT. Compared with the Non-HT group, the HT group had a higher LFR (0.47 (0.34-0.65) vs. 0.32 (0.07-0.56); P < 0.001). According to the binary logistic regression analysis, the LFR (aOR: 6.737; 95 % CI: 1.994-22.758; P = 0.002), Hypertension history (aOR: 2.231; 95 % CI: 1.201-4.142; P = 0.011), plasma FIB levels before MT (aOR: 0.641; 95 % CI: 0.456-0.902; P = 0.011), and the mismatch ratio (aOR: 0.990; 95 % CI: 0.980-0.999; P = 0.030) were independently associated with HT secondary to MT. The area under the curve of the regression model for predicting HT was 0.741. CONCLUSION: LFR, a ratio quantified via CTP, demonstrates potential as an independent risk factor of HT secondary to MT.

KEGG orthology prediction of bacterial proteins using natural language processing.

BACKGROUND: The advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing the capacity of manual curation. A large number of bacterial protein sequences remain unannotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, making it necessary to use auto annotation tools. These tools are now indispensable in the biological research landscape, bridging the gap between the vastness of unannotated sequences and meaningful biological insights. RESULTS: In this work, we propose a novel pipeline for KEGG orthology annotation of bacterial protein sequences that uses natural language processing and deep learning. To assess the effectiveness of our pipeline, we conducted evaluations using the genomes of two randomly selected species from the KEGG database. In our evaluation, we obtain competitive results on precision, recall, and F1 score, with values of 0.948, 0.947, and 0.947, respectively. CONCLUSIONS: Our experimental results suggest that our pipeline demonstrates performance comparable to traditional methods and excels in identifying distant relatives with low sequence identity. This demonstrates the potential of our pipeline to significantly improve the accuracy and comprehensiveness of KEGG orthology annotation, thereby advancing our understanding of functional relationships within biological systems.

A sensitivity-enhanced plasmonic sensing platform modified with Co(OH)2 nanosheets.

In the detection of biomolecules, surface plasmon resonance (SPR) sensors require high sensitivity. In this study, we propose a sensitivity-enhanced functionalized plasmonic interface based on Ag-TiO2-Co(OH)2 nanosheets structure. Compared to unmodified SPR sensors, the sensitivity of the sensor decorated with TiO2 and Co(OH)2 nanosheets is increased by 130.84%, reaching 5764.27 nm/RIU. This enhancement is attributed to the high refractive index of the coating, as well as the high specific surface area and abundant active sites provided by the synthesized Co(OH)2 nanosheets with a multi-grooved structure. Additionally, employing a double-antibody sandwich method, the antibody-functionalized plasmonic interface enables specific detection of human serum albumin (HSA). The linear response of this sensor was in the wide range of 0.4-150 µM, and the LOD reached 154.89 nM(KD is approximately 1.73 × 10-6 M). This novel SPR sensor offers a new strategy for biochemical sensing and provides a highly sensitive platform for immunoassays.

Synthesis, biological evaluation and docking studies of N-substituted resveratrol derivatives.

A total of 19 resveratrol derivatives, including 12 imines and 7 amines, were synthesized, among which compounds 1, 5, 6, 7', 11', and 13 are new compounds. The anti-inflammatory and antitumor activities of these compounds were evaluated in vitro. The results revealed that compounds 1, 6, 8', 12, and 12' exhibited significant inhibitory effects (> 50%) on NO production at the concentration of 10 µM and their NO production inhibitory activities have a significant concentration-dependent ability. Additionally, compounds 8' and 12' showed promising COX-2 inhibitory activity, and the molecular docking analysis indicated their stable binding to multiple amino acid residues within the active pocket of COX-2 through hydrogen bonding. Moreover, compound 12' exhibited inhibitory effects on various tumor cell lines and induced apoptosis in MCF-7 breast cancer cells, which was not observed with resveratrol alone. Therefore, the N-substituted structural modification of resveratrol would have possibly enhanced the bioactivity of resveratrol and facilitated its application.

The impact of A-site cations on the crystal structure and magnetism of the new double perovskites ALaCoTeO6 (A = Na and K).

In this work, we report the structural and magnetic characterization of two new B-site rock-salt ordered double perovskites ALaCoTeO6 (A = K+ and Na+) with mixed A-site cations. KLaCoTeO6 crystallizes in the space group P4/nmm with a long-range ordering degree of 84.8% for the A-site K+/La3+ cations, whereas NaLaCoTeO6 adopts an unexpected triclinically distorted I1̄-structure with Na/La3+ disordering, validated by combined Rietveld refinements against high-resolution neutron diffraction data and Cu Kα1 X-ray powder diffraction data. Magnetic susceptibility at low temperatures shows clear antiferromagnetic (AFM) transitions for both compounds. KLaCoTeO6 exhibits the highest AFM transition temperature of 20 K amongst all the Co/Te-ordered 3C-type A2CoTeO6 (A = Pb2+, Sr2+, and Ca2+) and ALaCoTeO6 double perovskites due to its larger Co2+-O-Te6+ bond angle and A-site cationic ordering-induced larger distortion of the Co2+-based face-centered cubic sublattice. Moreover, we found that the average radius of the A-site cations plays a decisive role in the AFM transition temperatures of all these ordered double perovskites, that is, a larger A-site cation always results in a higher AFM transition temperature. This provides a strategy to subtly manipulate the magnetic properties of ordered double perovskites.