Multi-omics analysis of Streptomyces djakartensis strain MEPS155 reveal a molecular response strategy combating Ceratocystis fimbriata causing sweet potato black rot.

To investigate the potential antifungal mechanisms of rhizosphere Actinobacteria against Ceratocystis fimbriata in sweet potato, a comprehensive approach combining biochemical analyses and multi-omics techniques was employed in this study. A total of 163 bacterial strains were isolated from the rhizosphere soil of sweet potato. Among them, strain MEPS155, identified as Streptomyces djakartensis, exhibited robust and consistent inhibition of C. fimbriata mycelial growth in in vitro dual culture assays, attributed to both cell-free supernatant and volatile organic compounds. Moreover, strain MEPS155 demonstrated diverse plant growth-promoting attributes, including the production of indole-3-acetic acid, 1-aminocyclopropane-1-carboxylate deaminase, phosphorus solubilization, nitrogen fixation, and enzymatic activities such as cellulase, chitinase, and protease. Notably, strain MEPS155 exhibited efficacy against various sweet potato pathogenic fungi. Following the inoculation of strain MEPS155, a significant reduction (P < 0.05) in malondialdehyde content was observed in sweet potato slices, indicating a potential protective effect. The whole genome of MEPS155 was characterized by a size of 8,030,375 bp, encompassing 7234 coding DNA sequences and 32 secondary metabolite biosynthetic gene clusters. Transcriptomic analysis revealed 1869 differentially expressed genes in the treated group that cultured with C. fimbriata, notably influencing pathways associated with porphyrin metabolism, fatty acid biosynthesis, and biosynthesis of type II polyketide products. These alterations in gene expression are hypothesized to be linked to the production of secondary metabolites contributing to the inhibition of C. fimbriata. Metabolomic analysis identified 1469 potential differently accumulated metabolites (PDAMs) when comparing MEPS155 and the control group. The up-regulated PDAMs were predominantly associated with the biosynthesis of various secondary metabolites, including vanillin, myristic acid, and protocatechuic acid, suggesting potential inhibitory effects on plant pathogenic fungi. Our study underscores the ability of strain S. djakartensis MEPS155 to inhibit C. fimbriata growth through the production of secretory enzymes or secondary metabolites. The findings contribute to a theoretical foundation for future investigations into the role of MEPS155 in postharvest black rot prevention in sweet potato.

Computer-aided designing of a novel multi­epitope DNA vaccine against severe fever with thrombocytopenia syndrome virus.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne viral disease caused by the SFTS virus (Dabie bandavirus), which has become a substantial risk to public health. No specific treatment is available now, that calls for an effective vaccine. Given this, we aimed to develop a multi-epitope DNA vaccine through the help of bioinformatics. The final DNA vaccine was inserted into a special plasmid vector pVAX1, consisting of CD8+ T cell epitopes, CD4+ T cell epitopes and B cell epitopes (six epitopes each) screened from four genome-encoded proteins--nuclear protein (NP), glycoprotein (GP), RNA-dependent RNA polymerase (RdRp), as well as nonstructural protein (NSs). To ascertain if the predicted structure would be stable and successful in preventing infection, an immunological simulation was run on it. In conclusion, we designed a multi-epitope DNA vaccine that is expected to be effective against Dabie bandavirus, but in vivo trials are needed to verify this claim.

Preparation of the new peptide drug ACTY116-loaded in situ forming implants and evaluation of its efficacy in pulmonary arterial hypertension and right ventricular hypertrophy induced by SU5416/hypoxia in mice.

There is a lack of effective therapeutic drugs for pulmonary arterial hypertension. Previous studies have demonstrated the positive cardiovascular system protective effects of the new peptide ACTY116. However, its stability in ordinary aqueous solution injections is poor and its half-life in the body is short, which has hindered the development of preparations. This study aimed to prepare in situ forming implants (ISFIs) of the peptide ACTY116 and investigate its impact on pulmonary arterial hypertension. We prepared ISFIs using NMP/TA as a solvent and PLGA as a polymer. These ISFIs exhibited low viscosity, low toxicity and sustained release properties. In a mouse model of pulmonary hypertension induced by SU5416/hypoxia, both ISFIs and ACTY116 peptides effectively reduced pulmonary hypertension, cardiac hypertrophy and pulmonary blood vessel wall thickness. In conclusion, this study highlights the potential of ACTY116 as a treatment for pulmonary arterial hypertension and suggests that incorporating it into an in-situ gel implant could be a promising option.

Thermal self-crosslink after etching for regulated preparation of Ti3C2 type MXene membrane and its preliminary gas separation.

We present an innovative methodology for the synthesis of MXene membranes through a dual-stage process involving etching and subsequent thermal self-crosslinking. A molar ratio of 1 (Al3+):9 (F-) using HCl/LiF was employed to convert raw Ti3AlC2 (MAX phase) into MXene within 48 h at 40 °C. This procedure predominantly yielded monolayers distinguished by diameters exceeding 500 nm, elevated crystallinity and a high overall yield. Advanced characterization techniques, including FESEM, TEM, HRTEM, AFM, XPS, and FTIR, were utilized. Instrumental analysis confirmed the formation of MXene exhibiting a single-flake morphology with diameters exceeding 500 nm. These monolayers were intact and continuous, with smooth peripheries and a uniform thickness of 2.1 nm. The surfaces were predominantly composed of carbon (C), oxygen (O), and titanium (Ti) atoms, interconnected by chemical bonds such as C-Ti-O, C-Ti-OH, C-C, C-O, and Ti-O. In the subsequent phase, vacuum filtration facilitated the assembly of a self-supporting MXene membrane. Thermal treatment at 170 °C for 30 h resulted in the reinforcement of C-Ti-O bonds within the nanosheets, increasing their prevalence to 43.14 % and 19.47 %, respectively. This thermal regulation reduced the interlayer d-spacing from 4.33 to 3.54 Å, which significantly improved the gas separation efficiency beyond the Knudsen diffusion limit, as demonstrated by the αH2/CF4 value exceeding 23.0.

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies.

In this article, we develop CausalEGM, a deep learning framework for nonlinear dimension reduction and generative modeling of the dependency among covariate features affecting treatment and response. CausalEGM can be used for estimating causal effects in both binary and continuous treatment settings. By learning a bidirectional transformation between the high-dimensional covariate space and a low-dimensional latent space and then modeling the dependencies of different subsets of the latent variables on the treatment and response, CausalEGM can extract the latent covariate features that affect both treatment and response. By conditioning on these features, one can mitigate the confounding effect of the high dimensional covariate on the estimation of the causal relation between treatment and response. In a series of experiments, the proposed method is shown to achieve superior performance over existing methods in both binary and continuous treatment settings. The improvement is substantial when the sample size is large and the covariate is of high dimension. Finally, we established excess risk bounds and consistency results for our method, and discuss how our approach is related to and improves upon other dimension reduction approaches in causal inference.

Counteracting TGM2 by a Fibroin peptide ameliorated Adriamycin-induced nephropathy via regulation of lipid metabolism through PANX1-PPAR α/PANK1 pathway.

Peptide drug discovery for the treatment of chronic kidney disease (CKD) has attracted much attention in recent years due to the urge to find novel drugs and mechanisms to delay the progression of the disease. In this study, we identified a novel short peptide (named YR-7, primary sequence 'YEVEDYR') from the natural Fibroin protein, and demonstrated that it significantly alleviated pathological renal changes in ADR-induced nephropathy. PANX1 was identified as the most notably upregulated component by RNA-sequencing. Further analysis showed that YR-7 alleviated the accumulation of lipid droplets via regulation of the lipid metabolism-related proteins PPAR α and PANK1. Using chemical proteomics, fluorescence polarization, microscale thermophoresis, surface plasmon resonance, and molecular docking, YR-7 was proven to directly bind to ß-barrel domains of TGM2 protein to inhibit lipid accumulation. TGM2 knockdown in vivo increased the protein levels of PPAR α and PANK1 while decreased the levels of fibrotic-related proteins to alleviate nephropathy. In vitro, overexpression TGM2 reversed the protective effects of YR-7. Co-immunoprecipitation indicated that TGM2 interacted with PANX1 to promote lipid deposition, and pharmacological inhibition or knockdown of PANX1 decreased the levels of PPAR α and PANK1 induced by ADR. Taken together, our findings revealed that TGM2-PANX1 interaction in promoting lipid deposition may be a new signaling in promoting ADR-induced nephropathy. And a novel natural peptide could ameliorate renal fibrosis through TGM2-PANX1-PPAR α/PANK1 pathway, which highlight the potential of it in the treatment of CKD.

Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.

BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. This study aimed to establish novel multiclassification prediction models based on machine learning (ML) to predict the probability of malignancy in pulmonary nodules (PNs) and to compare with three published models. METHODS: Nine hundred fourteen patients with PNs were collected from four medical institutions (A, B, C and D), which were organized into tables containing clinical features, radiologic features and laboratory test features. Patients were divided into benign lesion (BL), precursor lesion (PL) and malignant lesion (ML) groups according to pathological diagnosis. Approximately 80% of patients in A (total/male: 632/269, age: 57.73 ± 11.06) were randomly selected as a training set; the remaining 20% were used as an internal test set; and the patients in B (total/male: 94/53, age: 60.04 ± 11.22), C (total/male: 94/47, age: 59.30 ± 9.86) and D (total/male: 94/61, age: 62.0 ± 11.09) were used as an external validation set. Logical regression (LR), decision tree (DT), random forest (RF) and support vector machine (SVM) were used to establish prediction models. Finally, the Mayo model, Peking University People's Hospital (PKUPH) model and Brock model were externally validated in our patients. RESULTS: The AUC values of RF model for MLs, PLs and BLs were 0.80 (95% CI: 0.73-0.88), 0.90 (95% CI: 0.82-0.99) and 0.75 (95% CI: 0.67-0.88), respectively. The weighted average AUC value of the RF model for the external validation set was 0.71 (95% CI: 0.67-0.73), and its AUC values for MLs, PLs and BLs were 0.71 (95% CI: 0.68-0.79), 0.98 (95% CI: 0.88-1.07) and 0.68 (95% CI: 0.61-0.74), respectively. The AUC values of the Mayo model, PKUPH model and Brock model were 0.68 (95% CI: 0.62-0.74), 0.64 (95% CI: 0.58-0.70) and 0.57 (95% CI: 0.49-0.65), respectively. CONCLUSIONS: The RF model performed best, and its predictive performance was better than that of the three published models, which may provide a new noninvasive method for the risk assessment of PNs.

Occupational Category and Professional Title Influencing the Knowledge, Attitudes and Practice (KAP) of Quality Training: A Cross-Sectional Survey From a Tertiary General Hospital.

Quality improvement is an international priority, and quality education and training are important parts of hospital quality management. The aim of this study was to understand the knowledge, attitudes and practices (KAP) and its influencing factors related to quality training in medical staff. A questionnaire survey was conducted by convenience sampling to assess the KAP of quality training in Taizhou Enze Medical Center. Principal component analysis was used to extract factors from the questionnaire. Descriptive statistics (frequency, median, mean), Kendall grade correlation analysis, and Mann-Whitney U tests were used to analyze the data. A total of 205 staff members participated in the questionnaire survey. For the 5 factors of the KAP scale, the highest score was factor F4, recognition and support for quality training (mean = 90.55, median = 100), followed by factor F3, perceived benefits (mean = 84.46, median = 85.65). Relatively lower scores were found for factor F2, quality knowledge learning and mastery (mean = 63.09, median = 63.89), and F5, quality management practices and sharing (mean = 82.07, median = 75.00). There was a correlation between the 5 factors. The scores of F2 (quality knowledge learning and mastery) for staff with senior professional titles were higher than those for staff with intermediate professional titles or below. The score of F3 (perceived benefits of quality training) in medical technicians and nurses was higher than in doctors and administrative personnel. Our findings showed that the respondents' attitude toward quality training was positive, but their knowledge mastery and practice behaviors should be further improved. Occupational category and professional title were the influencing factors of the quality training KAP. Therefore, hospital should conduct quality management training at a wider scope according to the competency requirements of different groups, and further optimize the improvement and innovation system.

Global, regional and national trends and impacts of natural floods, 1990-2022.

Objective: To assess global, regional and national trends in the impact of floods from 1990 to 2022 and determine factors influencing flood-related deaths. Methods: We used data on flood disasters from the International Disaster Database for 1990-2022 from 168 countries. We calculated the annual percentage change to estimate trends in the rates of people affected and killed by floods by study period, World Health Organization (WHO) region, country income level and flood type. We used multivariable logistic regression analysis to assess the factors associated with death from floods. Findings: From 1990 to 2022, 4713 floods were recorded in 168 countries, which affected > 3.2 billion people, caused 218 353 deaths and were responsible for more than 1.3 trillion United States dollars of economic losses. The WHO Western Pacific Region had the most people affected by floods (> 2.0 billion), accounting for 63.19% (2 024 599 380/3 203 944 965) of all affected populations. The South-East Asia Region had the most deaths (71 713, 32.84%). The African and Eastern Mediterranean Regions had the highest number of people affected and killed by floods per 100 000 population in 2022. The odds of floods causing more than 50 deaths were significantly higher in low-income countries (adjusted odds ratio: 14.34; 95% confidence interval: 7.46 to 30.04) compared with high-income countries. Numbers of people affected and mortality due to floods declined over time. Conclusion: Despite the decreases in populations affected and deaths, floods still have a serious impact on people and economies globally, particularly in lower-income countries. Action is needed to improve disaster risk management and flood mitigation.

Spatial-temporal distribution characteristics of pulmonary tuberculosis in eastern China from 2011 to 2021.

China is still among the 30 high-burden tuberculosis (TB) countries in the world. Few studies have described the spatial epidemiological characteristics of pulmonary TB (PTB) in Jiangsu Province. The registered incidence data of PTB patients in 95 counties of Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System. Three-dimensional spatial trends, spatial autocorrelation, and spatial-temporal scan analysis were conducted to explore the spatial clustering pattern of PTB. From 2011 to 2021, a total of 347,495 newly diagnosed PTB cases were registered. The registered incidence rate of PTB decreased from 49.78/100,000 in 2011 to 26.49/100,000 in 2021, exhibiting a steady downward trend (χ2 = 414.22, P < 0.001). The average annual registered incidence rate of PTB was higher in the central and northern regions. Moran's I indices of the registered incidence of PTB were all >0 (P< 0.05) except in 2016, indicating a positive spatial correlation overall. Local autocorrelation analysis showed that 'high-high' clusters were mainly distributed in northern Jiangsu, and 'low-low' clusters were mainly concentrated in southern Jiangsu. The results of this study assist in identifying settings and locations of high TB risk and inform policy-making for PTB control and prevention.

ABA-mediated regulation of rice grain quality and seed dormancy via the NF-YB1-SLRL2-bHLH144 Module.

Abscisic acid (ABA) plays a crucial role in promoting plant stress resistance and seed dormancy. However, how ABA regulates rice quality remains unclear. This study identifies a key transcription factor SLR1-like2 (SLRL2), which mediates the ABA-regulated amylose content (AC) of rice. Mechanistically, SLRL2 interacts with NF-YB1 to co-regulate Wx, a determinant of AC and rice quality. In contrast to SLR1, SLRL2 is ABA inducible but insensitive to GA. In addition, SLRL2 exhibits DNA-binding activity and directly regulates the expression of Wx, bHLH144 and MFT2. SLRL2 competes with NF-YC12 for interaction with NF-YB1. NF-YB1 also directly represses SLRL2 transcription. Genetic validation supports that SLRL2 functions downstream of NF-YB1 and bHLH144 in regulating rice AC. Thus, an NF-YB1-SLRL2-bHLH144 regulatory module is successfully revealed. Furthermore, SLRL2 regulates rice dormancy by modulating the expression of MFT2. In conclusion, this study revealed an ABA-responsive regulatory cascade that functions in both rice quality and seed dormancy.

Effectiveness, cost, and safety of four regimens recommended by WHO for RR/MDR-TB treatment: a cohort study in Eastern China.

BACKGROUND: To compare the effectiveness, cost, and safety of four regimens recommended by the World Health Organization (WHO) for rifampicin resistance/multidrug-resistance tuberculosis (RR/MDR-TB) Treatment in Eastern China. METHODS: We performed a cohort study among patients with RR/MDR between 2020 and 2022 in Jiangsu Province. The treatment success rate, cost, and drug adverse reaction rate were compared. RESULTS: Between 2020 and 2022, 253 RR/MDR-TB patients were enrolled in the study. 37 (14.62%), 76 (30.04%), 74 (29.25%), and 66 (26.09%) patients had the short-term regimens, the new long-term oral regimens, the new long-term injectable regimens, and the traditional long-term regimens, respectively. The treatment success rate was the highest among patients treated with the short-term regimen (75.68%) and was the lowest among patients treated with the traditional long-term regimens (60.61%). The estimated mean cost per favorable outcome was 142.61 thousand Chinese Yuan (CNY), and the short-term regimens showed the lowest cost in the four regimes (88.51 thousand CNY vs. 174.24 thousand CNY, 144.00 thousand CNY, and 134.98 thousand CNY). Incremental cost-effectiveness ratios of the short-term regimens, the new long-term oral regimen, and the new long-term injectable regimens were -3083.04, 6040.09, and 819.68 CNY compared to the traditional long-term regimens. CONCLUSIONS: For RR/MDR-TB patients in China who meet the criteria for short-term regimens, the short-term regimens were proven to be the most cost-effective of the four regimens recommended by WHO. For RR/MDR-TB patients in China who don't meet the criteria for short-term regimens, the new long-term injectable regimens are more cost-effective than the remaining two regimens.

This is the first study to evaluate the effectiveness, cost, and safety of four regimens recommended by the WHO for RR/MDR-TB treatment in China.For RR/MDR-TB patients in China who meet the criteria for the short-term regimens, the short-term regimens were proven to be the most cost-effective of the four regimens recommended by WHO.

Metabolomic and biochemical changes in the plasma and liver of toxic milk mice model of Wilson disease.

Wilson disease (WD) is an inherited disorder characterized by abnormal copper metabolism with complex pathological features. Currently, this mechanism of copper overload-induced hepatic injury remains unclear. In this study, male toxic milk (TX) mice were selected as experimental subjects. Copper levels and biochemical indices were measured by atomic absorption spectroscopy (AAS) and kits. Liver tissue ultrastructure was observed by hematoxylin-eosin (H&E), sirius red staining and transmission electron microscopy. Plasma and liver metabolic profiles of TX mice were characterized by untargeted metabolomics. In addition, the expression of enzymes related to arachidonic acid metabolism in liver tissue was detected by Western blotting. The results showed the excessive copper content, concomitant oxidative stress, and hepatic tissue structural damage in TX mice. Seventy-eight metabolites were significantly different in WD, mainly involved in the metabolism of arachidonic acid, glycerophospholipids, sphingolipids, niacin and nicotinamide, and phenylalanine. Furthermore, the arachidonic acid metabolic pathway is an important pathway involved in WD metabolism. The level of arachidonic acid in the liver of TX mice was significantly lower (p < 0.01) compared to the control group. The expression of cytoplasmic phospholipase A2 (cPLA2) and arachidonic acid 12-lipoxygenase (ALOX12), related to the arachidonic acid metabolic pathway, was significantly different in the liver of TX mice (p < 0.01). Modulation of the arachidonic acid metabolic pathway could be a potential therapeutic strategy to alleviate WD symptoms.

Deciphering the role of female reproductive tract microbiome in reproductive health: a review.

Relevant studies increasingly indicate that female reproductive health is confronted with substantial challenges. Emerging research has revealed that the microbiome interacts with the anatomy, histology, and immunity of the female reproductive tract, which are the cornerstone of maintaining female reproductive health and preventing adverse pregnancy outcomes. Currently, the precise mechanisms underlying their interaction and impact on physiological functions of the reproductive tract remain elusive, constituting a prominent area of investigation within the field of female reproductive tract microecology. From this new perspective, we explore the mechanisms of interactions between the microbiome and the anatomy, histology, and immunity of the female reproductive tract, factors that affect the composition of the microbiome in the female reproductive tract, as well as personalized medicine approaches in managing female reproductive tract health based on the microbiome. This study highlights the pivotal role of the female reproductive tract microbiome in maintaining reproductive health and influencing the occurrence of reproductive tract diseases. These findings support the exploration of innovative approaches for the prevention, monitoring and treatment of female reproductive tract diseases based on the microbiome.

Peroxymonosulfate enhanced photocatalytic degradation of organic dye by metal-free TpTt-COF under visible light irradiation.

Recently, the activation of persulfate (PDS) by non-metallic photocatalysts under visible light has attracted significant interest in applications in environmental remediation. This study presents a pioneering investigation into the combined application of the TpTt-COF and PMS for visible light degradation of organic dyes. Synthesized orange TpTt-COF monomers exhibit exceptional crystallinity, a 2D structure, and notable stability in harsh conditions. The broad visible light absorption around a wavelength of 708 nm. The TpTt-COF emerges as a promising candidate for photocatalytic dye degradation. The study addresses high charge recombination in the TpTt-COF, highlighting the crucial role of its electron donor and acceptor for the PMS activation. Comparative analyses against traditional photocatalytic materials, such as the metal-free carbon-based material g-C3N4 and transition metal-containing TiO2, demonstrate TpTt-COF's superior performance, generating diverse free radicals. In simulated experiments, the TpTt-COF's degradation rate surpasses PMS-combined g-C3N4 by 13.9 times. and 1.6 times higher than the TpTt-COF alone. Remarkably, the TpTt-COF maintains high activity under harsh environments. Investigations into the degradation mechanism and the TpTt-COF's reusability reveal its efficiency and stability. Under visible light, TpTt-COF facilitates efficient electron-hole separation. Combining the TpTt-COF with PMS produces various radicals, ensuring effective separation and a synergistic effect. Radical quenching experiments confirm the pivotal role of O2-· radicals, while ·OH and SO4-· radicals intensify the degradation. After five cycles, TpTt-COF maintains an impressive 83.2% degradation efficiency. This study introduces an efficient photocatalytic system mediated by PMS and valuable insights into governing mechanisms for organic pollutant degradation in water environments.

Targeting estrogen mediated CYP4F2/CYP4F11-20-HETE metabolic disorder decelerates tumorigenesis in ER+ breast cancer.

Purpose: As the most common subset of breast cancer (BC), estrogen receptor positive (ER+) BC accounting for 80% of cases, has become a global public health concern. The female hormone estrogen (E2) unequivocally drives ER + breast malignancies. The reasons that estrogen affects BC development has long been considered, yet further study remains to be conducted of the molecular events in the E2-estrogen receptor α (ERα) signaling pathway in ER + BC progression, especially lipid metabolism, so providing more options for tailored and individualized therapy. Our aim is to find out new targets and clinical biomarkers for ER + breast cancer treatment from the perspective of lipid metabolism. Methods: Lipid metabolomics profiling was used to examine the membrane phospholipid stimulated by E2. Clinical BC samples were used to assess the association of CYP4F2, CYP4F11 expression with clinicopathological characteristics and patient outcomes. Some inhibitors of main enzymes in AA metabolism were used combined with E2 to assess roles of CYP4F2/CYP4F11 in the progression of ER + BC. CYP4F2, CYP4F11 overexpression and knockdown BC cell lines were employed to examine the effects of CYP4F2, CYP4F11 on cellular proliferation, apoptosis and tumor growth. Western blotting, qPCR, Immunohistochemical staining and flow cytometry were also conducted to determine the underlying mechanisms related to CYP4F2, CYP4F11 function. Results: The activation of the CYP450 signaling pathway in arachidonic acid metabolism contributed to ER + BC tumorigenesis. In ER + BC, CYP4F2 and CYP4F11 overexpression induced by E2 could promote cancer cell proliferation and resistance to apoptosis by producing the metabolite 20-HETE and activating the antiapoptotic protein Bcl-2. CYP4F2 and CYP4F11 elevation correlates with poorer overall survival and disease-free survival in ER + BC patients. Conclusion: CYP4F2, CYP4F11 and their metabolite 20-HETE could serve as effective prognostic markers and attractive therapeutic targets for novel anticancer drug development about ER + BC.

OTUB1/NDUFS2 axis promotes pancreatic tumorigenesis through protecting against mitochondrial cell death.

Pancreatic cancer is one of the most fatal cancers in the world. A growing number of studies have begun to demonstrate that mitochondria play a key role in tumorigenesis. Our previous study reveals that NDUFS2 (NADH: ubiquinone oxidoreductase core subunit S2), a core subunit of the mitochondrial respiratory chain complex I, is upregulated in Pancreatic adenocarcinoma (PAAD). However, its role in the development of PAAD remains unknown. Here, we showed that NDUFS2 played a critical role in the survival, proliferation and migration of pancreatic cancer cells by inhibiting mitochondrial cell death. Additionally, protein mass spectrometry indicated that the NDUFS2 was interacted with a deubiquitinase, OTUB1. Overexpression of OTUB1 increased NDUFS2 expression at the protein level, while knockdown of OTUB1 restored the effects in vitro. Accordingly, overexpression and knockdown of OTUB1 phenocopied those of NDUFS2 in pancreatic cancer cells, respectively. Mechanically, NDUFS2 was deubiquitinated by OTUB1 via K48-linked polyubiquitin chains, resulted in an elevated protein stability of NDUFS2. Moreover, the growth of OTUB1-overexpressed pancreatic cancer xenograft tumor was promoted in vivo, while the OTUB1-silenced pancreatic cancer xenograft tumor was inhibited in vivo. In conclusion, we revealed that OTUB1 increased the stability of NDUFS2 in PAAD by deubiquitylation and this axis plays a pivotal role in pancreatic cancer tumorigenesis and development.

Cost-Effectiveness of First-Line Atezolizumab versus Chemotherapy in Non-Small-Cell Lung Cancer Patients Ineligible for Platinum-Containing Regimens.

Purpose: The IPSOS study provided evidence supporting the efficacy and tolerability of first-line atezolizumab compared to single-agent chemotherapy for non-small-cell lung cancer (NSCLC) patients ineligible for treatment with a platinum-containing regimen. This study aimed to assess the cost-effectiveness of atezolizumab specifically in this population, considering the perspective of the Chinese healthcare system. Patients and Methods: In this analysis, a three-state Markov model was utilized. The survival data were derived from the IPSOS clinical trial. Direct medical costs and utility values were collected from national authoritative database and published literature. The primary outcomes were costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratio (ICER). To ensure the robustness of our model, both one-way and probabilistic sensitivity analyses were conducted. Results: Atezolizumab monotherapy led to an increase in costs of $4139.23 compared to single-agent chemotherapy. Additionally, it resulted in a gain of 0.14 QALYs, leading to an ICER of $29,365.79 per QALY, which was below the willingness-to-pay threshold of $36,066 per QALY used in the model. One-way sensitivity analyses revealed cost of atezolizumab and utility of progressive disease (PD) as major influencing factors for ICER. Furthermore, probabilistic sensitivity analyses confirmed our base-case results. Conclusion: From the perspective of the Chinese healthcare system, atezolizumab emerges as a cost-effective choice for the first-line treatment of NSCLC patients ineligible for platinum-based chemotherapy.

Siamese deep learning video flow cytometry for automatic and label-free clinical cervical cancer cell analysis.

Automatic and label-free screening methods may help to reduce cervical cancer mortality rates, especially in developing regions. The latest advances of deep learning in the biomedical optics field provide a more automatic approach to solving clinical dilemmas. However, existing deep learning methods face challenges, such as the requirement of manually annotated training sets for clinical sample analysis. Here, we develop Siamese deep learning video flow cytometry for the analysis of clinical cervical cancer cell samples in a smear-free manner. High-content light scattering images of label-free single cells are obtained via the video flow cytometer. Siamese deep learning, a self-supervised method, is built to introduce cell lineage cells into an analysis of clinical cells, which utilizes generated similarity metrics as label annotations for clinical cells. Compared with other deep learning methods, Siamese deep learning achieves a higher accuracy of up to 87.11%, with about 5.62% improvement for label-free clinical cervical cancer cell classification. The Siamese deep learning video flow cytometry demonstrated here is promising for automatic, label-free analysis of many types of cells from clinical samples without cell smears.

Label-Free Light Scattering Imaging with Purified Brownian Motion Differentiates Small Extracellular Vesicles in Cell Microenvironments.

Small extracellular vesicles (sEVs) are heterogeneous biological nanoparticles (NPs) with wide biomedicine applications. Tracking individual nanoscale sEVs can reveal information that conventional microscopic methods may lack, especially in cellular microenvironments. This usually requires biolabeling to identify single sEVs. Here, we developed a light scattering imaging method based on dark-field technology for label-free nanoparticle diffusion analysis (NDA). Compared with nanoparticle tracking analysis (NTA), our method was shown to determine the diffusion probabilities of a single NP. It was demonstrated that accurate size determination of NPs of 41 and 120 nm in diameter is achieved by purified Brownian motion (pBM), without or within the cell microenvironments. Our pBM method was also shown to obtain a consistent size estimation of the normal and cancerous plasma-derived sEVs without and within cell microenvironments, while cancerous plasma-derived sEVs are statistically smaller than normal ones. Moreover, we showed that the velocity and diffusion coefficient are key parameters for determining the diffusion types of the NPs and sEVs in a cancerous cell microenvironment. Our light scattering-based NDA and pBM methods can be used for size determination of NPs, even in cell microenvironments, and also provide a tool that may be used to analyze sEVs for many biomedical applications.