The sensitivity and significance analysis of parameters in the model of pH regulation on lactic acid production by Lactobacillus bulgaricus.

BACKGROUND: The excessive production of lactic acid by L. bulgaricus during yogurt storage is a phenomenon we are always tried to prevent. The methods used in industry either control the post-acidification inefficiently or kill the probiotics in yogurt. Genetic methods of changing the activity of one enzyme related to lactic acid metabolism make the bacteria short of energy to growth, although they are efficient ways in controlling lactic acid production. RESULTS: A model of pH-induced promoter regulation on the production of lactic acid by L. bulgaricus was built. The modelled lactic acid metabolism without pH-induced promoter regulation fitted well with wild type L. bulgaricus (R2LAC = 0.943, R2LA = 0.942). Both the local sensitivity analysis and Sobol sensitivity analysis indicated parameters Tmax, GR, KLR, S, V0, V1 and dLR were sensitive. In order to guide the future biology experiments, three adjustable parameters, KLR, V0 and V1, were chosen for further simulations. V0 had little effect on lactic acid production if the pH-induced promoter could be well induced when pH decreased to its threshold. KLR and V1 both exhibited great influence on the producing of lactic acid. CONCLUSIONS: The proposed method of introducing a pH-induced promoter to regulate a repressor gene could restrain the synthesis of lactic acid if an appropriate strength of promoter and/or an appropriate strength of ribosome binding sequence (RBS) in lacR gene has been designed.

Effect of 3D laparoscopy versus traditional laparotomy on serum tumor markers and coagulation function in patients with early-stage endometrial cancer.

OBJECTIVES: To investigate the impact of Three-Dimensional (3D) laparoscopy compared to traditional laparotomy on serum tumor markers and coagulation function in patients diagnosed with early-stage Endometrial Cancer (EC). METHOD: The authors retrospectively analyzed the clinical data of 75 patients diagnosed with early-stage EC and categorized them into two groups based on the surgical techniques employed. The 3D group consisted of 36 patients who underwent 3D laparoscopic surgery, while the Laparotomy group comprised 39 patients who underwent traditional laparotomy. The authors then compared the alterations in serum tumor markers and coagulation function between the two groups. RESULTS: Postoperatively, serum levels of CA125, CA199, and HE4 were notably reduced in both groups on the third day, with the levels being more diminished in the 3D group than in the Laparotomy Group (p < 0.05). Conversely, FIB levels escalated significantly in both groups on the third-day post-surgery, with a more pronounced increase in the 3D group. Additionally, PT and APTT durations were reduced and were more so in the 3D group than in the laparotomy group (p < 0.05). CONCLUSIONS: When juxtaposed with traditional laparotomy, 3D laparoscopic surgery for early-stage EC appears to be more efficacious, characterized by reduced complications, and expedited recovery. It can effectively mitigate serum tumor marker levels, attenuate the inflammatory response and damage to immune function, foster urinary function recovery, and enhance the quality of life. However, it exerts a more significant influence on the patient's coagulation parameters, necessitating meticulous prevention and treatment strategies for thromboembolic events in clinical settings.

T cell-mediated tumor killing sensitivity gene signature-based prognostic score for acute myeloid leukemia.

BACKGROUND AND OBJECTIVE: Acute myeloid leukemia (AML) is an aggressive, heterogenous hematopoetic malignancies with poor long-term prognosis. T-cell mediated tumor killing plays a key role in tumor immunity. Here, we explored the prognostic performance and functional significance of a T-cell mediated tumor killing sensitivity gene (GSTTK)-based prognostic score (TTKPI). METHODS: Publicly available transcriptomic data for AML were obtained from TCGA and NCBI-GEO. GSTTK were identified from the TISIDB database. Signature GSTTK for AML were identified by differential expression analysis, COX proportional hazards and LASSO regression analysis and a comprehensive TTKPI score was constructed. Prognostic performance of the TTKPI was examined using Kaplan-Meier survival analysis, Receiver operating curves, and nomogram analysis. Association of TTKPI with clinical phenotypes, tumor immune cell infiltration patterns, checkpoint expression patterns were analysed. Drug docking was used to identify important candidate drugs based on the TTKPI-component genes. RESULTS: From 401 differentially expressed GSTTK in AML, 24 genes were identified as signature genes and used to construct the TTKPI score. High-TTKPI risk score predicted worse survival and good prognostic accuracy with AUC values ranging from 75 to 96%. Higher TTKPI scores were associated with older age and cancer stage, which showed improved prognostic performance when combined with TTKPI. High TTKPI was associated with lower naïve CD4 T cell and follicular helper T cell infiltrates and higher M2 macrophages/monocyte infiltration. Distinct patterns of immune checkpoint expression corresponded with TTKPI score groups. Three agents; DB11791 (Capmatinib), DB12886 (GSK-1521498) and DB14773 (Lifirafenib) were identified as candidates for AML. CONCLUSION: A T-cell mediated killing sensitivity gene-based prognostic score TTKPI showed good accuracy in predicting survival in AML. TTKPI corresponded to functional and immunological features of the tumor microenvironment including checkpoint expression patterns and should be investigated for precision medicine approaches.

Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia.

Background: Acute Myeloid Leukemia (AML) exhibits a wide array of phenotypic manifestations, progression patterns, and heterogeneous responses to immunotherapies, suggesting involvement of complex immunobiological mechanisms. This investigation aimed to develop an integrated prognostic model for AML by incorporating cancer driver genes, along with clinical and phenotypic characteristics of the disease, and to assess its implications for immunotherapy responsiveness. Methods: Critical oncogenic driver genes linked to survival were identified by screening primary effector and corresponding gene pairs using data from The Cancer Genome Atlas (TCGA), through univariate Cox proportional hazard regression analysis. This was independently verified using dataset GSE37642. Primary effector genes were further refined using LASSO regression. Transcriptomic profiling was quantified using multivariate Cox regression, and the derived prognostic score was subsequently validated. Finally, a multivariate Cox regression model was developed, incorporating the transcriptomic score along with clinical parameters such as age, gender, and French-American-British (FAB) classification subtype. The 'Accurate Prediction Model of AML Overall Survival Score' (APMAO) was developed and subsequently validated. Investigations were conducted into functional pathway enrichment, alterations in the gene mutational landscape, and the extent of immune cell infiltration associated with varying APMAO scores. To further investigate the potential of APMAO scores as a predictive biomarker for responsiveness to cancer immunotherapy, we conducted a series of analyses. These included examining the expression profiles of genes related to immune checkpoints, the interferon-gamma signaling pathway, and m6A regulation. Additionally, we explored the relationship between these gene expression patterns and the Tumor Immune Dysfunction and Exclusion (TIDE) dysfunction scores. Results: Through the screening of 95 cancer genes associated with survival and 313 interacting gene pairs, seven genes (ACSL6, MAP3K1, CHIC2, HIP1, PTPN6, TFEB, and DAXX) were identified, leading to the derivation of a transcriptional score. Age and the transcriptional score were significant predictors in Cox regression analysis and were integral to the development of the final APMAO model, which exhibited an AUC greater than 0.75 and was successfully validated. Notable differences were observed in the distribution of the transcriptional score, age, cytogenetic risk categories, and French-American-British (FAB) classification between high and low APMAO groups. Samples with high APMAO scores demonstrated significantly higher mutation rates and pathway enrichments in NFKB, TNF, JAK-STAT, and NOTCH signaling. Additionally, variations in immune cell infiltration and immune checkpoint expression, activation of the interferon-γ pathway, and expression of m6A regulators were noted, including a negative correlation between CD160, m6A expression, and APMAO scores. Conclusion: The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes. It was linked to unique phenotypic characteristics, distinctive immune and mutational profiles, and patterns of expression for markers related to immunotherapy sensitivity. These observations suggest the potential for facilitating precision immunotherapy and advocate for its exploration in upcoming clinical trials.

A postoperative tumor-specific death prediction model for patients with endometrial cancer: a retrospective study.

Background: Endometrial cancer (EC) is an epithelial malignancy occurring in the endometrium, with a 5-year mortality rate of above 10%. However, there is currently a lack of studies exploring the potential of a predictive model of tumor-specific death after surgery in these patients. Methods: From January 2015 to December 2017, data related to 482 patients with EC admitted to the Dushu Lake Hospital Affiliated to Soochow University were analyzed. Patients were divided into death (n=62) and survival (n=420) groups according to whether tumor-specific death occurred at 5 years postoperatively or not. The clinical characteristics of the two groups were compared, and the risk factors for tumor-specific death in patients with EC 5 years after surgery were investigated by logistics regression analysis. A nomogram prediction model was established according to the relevant risk factors. Results: Tumor size, Ki-67 positive rate, Federation International of Gynecology and Obstetrics (FIGO) stage, and the rate of vascular tumor thrombus between the two groups (P<0.05) were found to be the statistically significant factors. Positive Ki-67, tumor size >3.35 cm, stage III, and vascular tumor thrombus were factors that influenced the tumor-specific death at 5 years after surgery (P<0.05). The predictive model obtained an area under the receiver operating characteristic (ROC) curves in the training and verification sets of 0.847 [95% confidence interval (CI): 0.779-0.916] and 0.886 (95% CI: 0.803-0.969), respectively. Conclusions: The nomogram prediction model, which was established in this study, was proved to be valuable in predicting tumor-specific death 5 years after the surgery in patients with EC.

Construction of a risk model and deep learning network based on patients with active pulmonary tuberculosis and pulmonary inflammation.

Most patients with active pulmonary tuberculosis (TB) are difficult to be differentiated from pneumonia (PN), especially those with acid-fast bacillus smear-negative (AFB-) and interferon-γ release assay-positive (IGRA+) results. Thus, the aim of the present study was to develop a risk model of low-cost and rapid test for the diagnosis of AFB- IGRA+ TB from PN. A total of 41 laboratory variables of 204 AFB- IGRA+ TB and 156 PN participants were retrospectively analyzed. Candidate variables were identified by t-statistic test and univariate logistic model. The logistic regression analysis was used to construct the multivariate risk model and nomogram with internal and external validation. A total of 13 statistically differential variables were compared between AFB- IGRA+ TB and PN by false discovery rate (FDR) and odds ratio (OR). By integrating five variables, including age, uric acid (UA), albumin (ALB), hemoglobin (Hb) and white blood cell counts (WBC), a multivariate risk model with a concordance index (C-index) of 0.7 (95% CI: 0.61, 0.8) was constructed. The nomogram showed that UA and Hb acted as protective factors with an OR <1, while age, WBC and ALB were risk factors for TB occurrence. Internal and external validation revealed that nomogram prediction was consistent with the actual observations. Collectively, it was revealed that an integration of five biomarkers (age, UA, ALB, Hb and WBC) may be used to quickly predict TB in AFB- IGRA+ clinical samples from PN.

A comprehensive prognostic score for head and neck squamous cancer driver genes and phenotype traits.

BACKGROUND: Head and neck squamous cancer (HNSCC) presents variable phenotype and progression features. Clinically applicable, high-accuracy multifactorial prognostic models for HNSCC survival outcomes are warranted and an active area of research. This study aimed to construct a comprehensive prognostic tool for HNSCC overall survival by integrating cancer driver genes with tumor clinical and phenotype information. METHODS: Key overall survival-related cancer driver genes were screened from among main effector and reciprocal gene pairs using TCGA data using univariate Cox proportional hazard regression analysis. Independent validation was performed using the GSE41613 dataset. The main effector genes among these were selected using LASSO regression and transcriptome score modeling was performed using multivariate Cox regression followed by validation analysis of the prognostic score. Next, multivariate Cox regression analysis was performed using the transcriptome score combined with age, grade, gender, and stage. An 'Accurate Prediction Model of HNSCC Overall Survival Score' (APMHO) was computed and validated. Enriched functional pathways, gene mutational landscape, immune cell infiltration, and immunotherapy sensitivity markers associated with high and low APMHO scores were analyzed. RESULTS: Screening 107 overall survival-related cancer genes and 402 interacting gene pairs, 6 genes: CRLF2, HSP90AA1, MAP2K1, PAFAH1B2, MYCL and SET genes, were identified and a transcriptional score was obtained. Age, stage and transcriptional score were found to be significant predictors in Cox regression analysis and used to construct a final APMHO model showing an AUC > 0.65 and validated. Transcriptional score, age, pathologic_N, pathologic_T, stage, and TCGA_subtype were significantly different in distribution between high and low APMHO groups. High APMHO samples showed significantly higher mutation rate, enriched tumor-related pathways including Hypoxia, unfold_protein_response, Glycolysis, and mTORC1 signaling, along with differences in immune cell infiltration and immune checkpoint, interferon-γ pathway and m6A regulator expression patterns. CONCLUSION: The APMHO score combining transcriptional and clinical variables showed good prognostic ability for HNSCC overall survival outcomes and was associated with different patterns of phenotypical features, immune and mutational landscape, and immunotherapy sensitivity marker expression. Future studies should validate this score in independent clinical cohorts.

Investigation on the contents of heat-induced hazards in commercial nuts.

The purpose was to investigate the contents of heat-induced hazards by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in 44 commercial nuts. Results showed that content ranges of Acrylamide (AA), 5-hydroxymethylfurfural (5-HMF), Nε-carboxymethyl-lysine (CML), Nε-carboxyethyl-lysine (CEL), 3-Deoxyglucosone (3-DG), Glyoxal (GO), and Methylglyoxal (MGO) were ND-123.57 µg/kg, 0.57-213.42 mg/kg, 3.18-18.67 mg/kg, 3.98-57.85 mg/kg, 1.5-133.86 mg/kg, 0.45-1.59 mg/kg and 0.29-13.84 mg/kg, respectively. Sunflower seeds contained more heat-induced hazards followed by pistachios, cashews, almonds, walnuts and hazelnuts. The content of 5-HMF was positively correlated with the content of 3-DG. CML exhibited positive correlation with content of GO while no correlation between CEL and MGO. Higher levels of 3-DG and 5-HMF were observed in nuts produced with sugar and honey. Deep processing had a stronger promoting effect on CML and CEL formation. These data could provide a crucial guide for consumers to select nut products which might reduce heat-induced hazards intake.

Mycobacterium tuberculosis Utilizes Host Histamine Receptor H1 to Modulate Reactive Oxygen Species Production and Phagosome Maturation via the p38MAPK-NOX2 Axis.

Tuberculosis (TB), which is caused by the single pathogenic bacterium, Mycobacterium tuberculosis, is among the top 10 lethal diseases worldwide. This situation has been exacerbated by the increasing number of cases of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB). Histamine is an organic nitrogenous compound that mediates a plethora of cell processes via different receptors. The expression of histamine receptor H1 (HRH1), one of the four histamine receptors identified to date was previously reported to be augmented by M. tuberculosis infection, although the underlying mechanism is unclear. In the present study, we applied confocal microscopy, flow cytometry, and Western blotting to show that HRH1 expression was enhanced in macrophages following mycobacterial infection. Furthermore, by combining techniques of gene knockdown, immunoprecipitation, intracellular bacterial burden analysis, fluorescence labeling, and imaging, we found that M. tuberculosis targeted the host HRH1 to suppress NOX2-mediated cROS production and inhibit phagosome maturation and acidification via the GRK2-p38MAPK signaling pathway. Our findings clarified the underlying mechanism of the M. tuberculosis and host HRH1 interaction and may provide useful information for the development of novel antituberculosis treatments. IMPORTANCE Once engulfed in macrophage phagosomes, M. tuberculosis adopts various strategies to take advantage of the host environment for its intracellular survival. Histamine is an organic nitrogen-containing compound that mediates a plethora of cellular processes via different receptors, but the crosstalk mechanism between M. tuberculosis and HRH1 in macrophages is not clear. Our results revealed that M. tuberculosis infection enhanced HRH1 expression, which in turn restrained macrophage bactericidal activity by modulating the GRK2-p38MAPK signaling pathway, inhibiting NOX2-mediated cROS production and phagosome maturation. Clarification of the underlying mechanism by which M. tuberculosis utilizes host HRH1 to favor its intracellular survival may provide useful information for the development of novel antituberculosis treatments.

Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019.

In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients' transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases.

Effect of 3D laparoscopy versus traditional laparotomy on serum tumor markers and coagulation function in patients with early-stage endometrial cancer

Abstract Objectives To investigate the impact of Three-Dimensional (3D) laparoscopy compared to traditional laparotomy on serum tumor markers and coagulation function in patients diagnosed with early-stage Endometrial Cancer (EC). Method The authors retrospectively analyzed the clinical data of 75 patients diagnosed with early-stage EC and categorized them into two groups based on the surgical techniques employed. The 3D group consisted of 36 patients who underwent 3D laparoscopic surgery, while the Laparotomy group comprised 39 patients who underwent traditional laparotomy. The authors then compared the alterations in serum tumor markers and coagulation function between the two groups. Results Postoperatively, serum levels of CA125, CA199, and HE4 were notably reduced in both groups on the third day, with the levels being more diminished in the 3D group than in the Laparotomy Group (p < 0.05). Conversely, FIB levels escalated significantly in both groups on the third-day post-surgery, with a more pronounced increase in the 3D group. Additionally, PT and APTT durations were reduced and were more so in the 3D group than in the laparotomy group (p < 0.05). Conclusions When juxtaposed with traditional laparotomy, 3D laparoscopic surgery for early-stage EC appears to be more efficacious, characterized by reduced complications, and expedited recovery. It can effectively mitigate serum tumor marker levels, attenuate the inflammatory response and damage to immune function, foster urinary function recovery, and enhance the quality of life. However, it exerts a more significant influence on the patient's coagulation parameters, necessitating meticulous prevention and treatment strategies for thromboembolic events in clinical settings.

The Pathway Analysis of Micrornas Regulated Drug-Resistant Responses in HeLa Cells.

Chemotherapy is the main strategy in the treatment of cancer; however, the development of drug-resistance is the obstacle in long-term treatment of cervical cancer. Cisplatin is one of the most common drugs used in cancer therapy. Recently, accumulating evidence suggests that miRNAs are involved in various bioactivities in oncogenesis. It is not unexpected that miRNAs play a key role in acquiring of drug-resistance in the progression of tumor. In this study, we induced and maintained four levels of cisplatin-resistant HeLa cell lines (HeLa/CR1, HeLa/CR2, HeLa/CR3, and HeLa/CR4). According to the previous studies and existing evidence, we selected five miRNAs (miR-183, miR-182, miR-30a, miR-15b, and miR-16) and their potential target mRNAs as our research targets. The real-time RT-PCR was adopted to detect the relative expression of miRNAs and their mRNAs. The results show that miR-182 and miR-15b were up-regulated in resistant cell lines, while miR-30a was significantly down-regulated. At the same time, their targets are related to drug resistance. Compared to their parent HeLa cell line, the expression of selected miRNAs in resistant cell lines altered. The alteration suggests that HeLa cell drug resistance is associated with distinct miRNAs, which indicates that miRNAs may be one of the therapy targets in the treatment of cervical cancer by sensitizing cell to chemotherapy. We suggested a possible network diagram based on the existing theory and the preliminary results of candidate miRNAs and their targets in HeLa cells during development of drug resistance.

Design and simulation of proportional biological operational Mu-circuit.

It is challenging yet desirable to quantitatively control the expression of a target gene in practice. We design a device-Proportional Biological Operational Mu-circuit (P-BOM) incorporating AND/OR gate and operational amplifier into one circuit and explore its behaviors through simulation. The results imply that will be possible to regulate input-output proportionally by manipulating the RBS of hrpR, hrpS, tetR and output gene and used in the sensing of environmental weak signals such as dioxins.