An Analysis of the Cost Variation Among Different Antimicrobial Agents: The Indian Scenario.

Background and objective Infectious diseases pose a substantial global health challenge, especially in developing countries where healthcare accessibility is limited. Pharmaceutical expenses constitute a significant share of out-of-pocket expenditure (60-90%). Hence, the affordability of medications becomes a critical determinant for patient compliance. This study focuses on the economic dynamics of antimicrobial agents. Methodology After collecting data from the Current Index of Medical Specialties (CIMS), different antimicrobial agents (AMAs) were assessed based on their cost per 10 tablets/10 capsules/one vial of injection. A comprehensive analysis was performed to assess the minimum and maximum costs for each medication across diverse pharmaceutical companies. Cost variation was assessed through both the cost ratio and percentage cost variation. The data were analyzed and represented using descriptive statistics Results Our findings indicate significant cost variations, with nitrofurantoin 100 mg tablet showcasing a staggering 1498.5% variation, followed by meropenem 500 mg vial at 473.91%. Conversely, the cotrimoxazole (sulfamethoxazole 800 mg + trimethoprim 160 mg) tablet exhibits a minimal 6.05% variation, underscoring the diversity in pricing strategies. The number of brands ranged from two to 62. Conclusions This study underscores the importance of considering cost variations in antimicrobial agents while prescribing the same. Doing so will not only address the economic challenges faced by patients but also help in improving compliance and reducing the risk of antimicrobial drug resistance. This approach advocates for a more economically sustainable and patient-centric healthcare ecosystem in India.

Genomic insights into cytokinin oxidase/dehydrogenase (CKX) gene family, identification, phylogeny and synteny analysis for its possible role in regulating seed number in Pigeonpea (Cajanus cajan (L.) Millsp.).

Cytokinin oxidase/dehydrogenase (CKX) regulates cytokinin levels in plants which are vital for plant growth and development. However, there is a paucity of evidence regarding their role in controlling embryo/seed development in pigeonpea. This comprehensive study provides information on the identification and characterization of CKX genes in pigeonpea. A genome-wide analysis identified 18 CKX genes, each with distinct structure, expression patterns, and possible diverse functions. Domain analysis revealed the presence of the sequences including FAD and CK-Binding domain, and subcellular localization analysis showed that almost 50 % of them reside within the nucleus. They were observed to be located unevenly on chromosome numbers 2, 4, 6, 7, and 11 with a majority of them present on the scaffolds. The 8 homologous pairs and various orthologous gene pairs provided further insights into their evolution pattern. Further, SNP/Indels variation in CKX genes and haplotype groups among contrasting genotypes for SNPP (seed number per pod) were analyzed. Spatiotemporal expression analysis revealed the significant expression pattern of CcCKX15, CcCKX17, and CcCKX2 in genotypes carrying low SNPP reiterating their possible role as negative regulators. These genes can be potential targets to undertake seed and biomass improvement in pigeonpea.

Endotypes of severe neutrophilic and eosinophilic asthma from multi-omics integration of U-BIOPRED sputum samples.

BACKGROUND: Clustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi-omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development. OBJECTIVES: To determine whether multi-omics integration of sputum leads to improved granularity of the molecular classification of severe asthma. METHODS: We analyzed six -omics data blocks-microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing-from induced sputum samples of 57 severe asthma patients, 15 mild-moderate asthma patients, and 13 healthy volunteers in the U-BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi-omics datasets of the 72 asthmatics. RESULTS: Five stable omics-associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL-22 cytokine activation, with the prediction of therapeutic response to anti-IL22 antibody therapy. CONCLUSION: Multi-omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high-dimensional interactions will contribute to a more comprehensive understanding of complex endotypes. KEY POINTS: Unsupervised clustering on sputum multi-omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL-22.

Application of Graph Models to the Identification of Transcriptomic Oncometabolic Pathways in Human Hepatocellular Carcinoma.

Whole-tissue transcriptomic analyses have been helpful to characterize molecular subtypes of hepatocellular carcinoma (HCC). Metabolic subtypes of human HCC have been defined, yet whether these different metabolic classes are clinically relevant or derive in actionable cancer vulnerabilities is still an unanswered question. Publicly available gene sets or gene signatures have been used to infer functional changes through gene set enrichment methods. However, metabolism-related gene signatures are poorly co-expressed when applied to a biological context. Here, we apply a simple method to infer highly consistent signatures using graph-based statistics. Using the Cancer Genome Atlas Liver Hepatocellular cohort (LIHC), we describe the main metabolic clusters and their relationship with commonly used molecular classes, and with the presence of TP53 or CTNNB1 driver mutations. We find similar results in our validation cohort, the LIRI-JP cohort. We describe how previously described metabolic subtypes could not have therapeutic relevance due to their overall downregulation when compared to non-tumoral liver, and identify N-glycan, mevalonate and sphingolipid biosynthetic pathways as the hallmark of the oncogenic shift of the use of acetyl-coenzyme A in HCC metabolism. Finally, using DepMap data, we demonstrate metabolic vulnerabilities in HCC cell lines.

Adrenal pheochromocytoma impacts three main pathways: cysteine-methionine, pyrimidine, and tyrosine metabolism. / è‚¾ä¸Šè ºå—œé“¬ç»†èƒžç˜¤å½±å“ä¸‰æ¡ä¸»è¦ä»£è°¢é€šè·¯ï¼šåŠèƒ±æ°¨é ¸-è›‹æ°¨é ¸ä»£è°¢ã€å˜§å•¶ä»£è°¢å’Œé ªæ°¨é ¸ä»£è°¢é€šè·¯.

Pheochromocytomas and paragangliomas (PPGLs) cause symptoms by altering the circulation levels of catecholamines and peptide hormones. Currently, the diagnosis of PPGLs relies on diagnostic imaging and the detection of catecholamines. In this study, we used ultra-performance liquid chromatography (UPLC)/quadrupole time-of-flight mass spectrometry (Q-TOF MS) analysis to identify and measure the perioperative differential metabolites in the plasma of adrenal pheochromocytoma patients. We identified differentially expressed genes by comparing the transcriptomic data of pheochromocytoma with the normal adrenal medulla. Through conducting two steps of metabolomics analysis, we identified 111 differential metabolites between the healthy group and the patient group, among which 53 metabolites were validated. By integrating the information of differential metabolites and differentially expressed genes, we inferred that the cysteine-methionine, pyrimidine, and tyrosine metabolism pathways were the three main metabolic pathways altered by the neoplasm. The analysis of transcription levels revealed that the tyrosine and cysteine-methionine metabolism pathways were downregulated in pheochromocytoma, whereas the pyrimidine pathway showed no significant difference. Finally, we developed an optimized diagnostic model of two metabolites, L-dihydroorotic acid and vanylglycol. Our results for these metabolites suggest that they may serve as potential clinical biomarkers and can be used to supplement and improve the diagnosis of pheochromocytoma.

Variations and inequities in access to cardiac diagnostic services in Ontario Canada.

OBJECTIVES: Echocardiography is an essential diagnostic modality known to have wide regional utilization variations. This study's objectives were to quantify regional variations and to examine the extent to which they are explained by differences in population age, sex, cardiac disease prevalence (CDP), and social determinants of health (SDH) risk. METHODS: This is an observational study of all echocardiography exams performed in Ontario in 2019/20 (n = 695,622). We measured regional variations in echocardiography crude rates and progressively standardized rates for population age, sex, CDP, and SDH risk. RESULTS: After controlling for differences in population age, sex, and CDP, Ontario's highest rate regions had echocardiography rates 57% higher than its lowest rate regions. Forty eight percent of total variation was not explained by differences in age, sex, and CDP. CDP increased with SDH risk. Access to most cardiac diagnostics was negatively correlated with SDH risk, while cardiac catheterization rates were positively correlated with SDH risk. CONCLUSION: Variations analysis that adjusts for age and sex only without including clinical measures of need are likely to overestimate the unwarranted portion of total variation. Substantial variations persisted despite a mandatory provider accreditation policy aimed at curtailing them. The associations between variations and SDH risks imply a need to redress access and outcome inequities.

Screening candidate genes for fruit size based on QTL-seq in Chinese jujube.

Introduction: Fruit size is an important economic trait affecting jujube fruit quality, which has always been the focus of marker-assisted breeding of jujube traits. However, despite a large number of studies have been carried out, the mechanism and key genes regulating jujube fruit size are mostly unknown. Methods: In this study, we used a new analysis method Quantitative Trait Loci sequencing (QTL-seq) (bulked segregant analysis) to screen the parents 'Yuhong' and 'Jiaocheng 5' with significant phenotypic differences and mixed offspring group with extreme traits of large fruit and small fruit, respectively, and, then, DNA mixed pool sequencing was carried out to further shortening the QTL candidate interval for fruit size trait and excavated candidate genes for controlling fruit size. Results: The candidate intervals related to jujube fruit size were mainly located on chromosomes 1, 5, and 10, and the frequency of chromosome 1 was the highest. Based on the QTL-seq results, the annotation results of ANNOVAR were extracted from 424 SNPs (single-nucleotide polymorphisms) and 164 InDels (insertion-deletion), from which 40 candidate genes were selected, and 37 annotated candidate genes were found in the jujube genome. Four genes (LOC107428904, LOC107415626, LOC125420708, and LOC107418290) that are associated with fruit size growth and development were identified by functional annotation of the genes in NCBI (National Center for Biotechnology Information). The genes can provide a basis for further exploration and identification on genes regulating jujube fruit size. Discussion: In summary, the data obtained in this study revealed that QTL intervals and candidate genes for fruit size at the genomic level provide valuable resources for future functional studies and jujube breeding.

Successful Multimodal Treatment of Intracranial Growing Teratoma Syndrome with Malignant Features.

Molecular analysis of the growing teratoma syndrome has not been extensively studied. Here, we report a 14-year-old boy with a growing mass during treatment for a mixed germ cell tumor of the pineal region. Tumor markers were negative; thus, growing teratoma syndrome was suspected. A radical resection via the occipital transtentorial approach was performed, and histopathological examination revealed a teratoma with malignant features. Methylation classifier analysis confirmed the diagnosis of teratoma, and DMRT1 loss and 12p gain were identified by copy number variation analysis, potentially elucidating the cause of growth and malignant transformation of the teratoma. The patient remains in remission after intense chemoradiation treatment as a high-risk germ cell tumor.

Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches.

BACKGROUND: Biomarkers and pathways associated with renal ischemia reperfusion injury (IRI) had not been well unveiled. This study was intended to investigate and summarize the regulatory networks for related hub genes. Besides, the immunological micro-environment features were evaluated and the correlations between immune cells and hub genes were also explored. METHODS: GSE98622 containing mouse samples with multiple IRI stages and controls was collected from the GEO database. Differentially expressed genes (DEGs) were recognized by the R package limma, and the GO and KEGG analyses were conducted by DAVID. Gene set variation analysis (GSVA) and weighted gene coexpression network analysis (WGCNA) had been implemented to uncover changed pathways and gene modules related to IRI. Besides the known pathways such as apoptosis pathway, metabolic pathway, and cell cycle pathways, some novel pathways were also discovered to be critical in IRI. A series of novel genes associated with IRI was also dug out. An IRI mouse model was constructed to validate the results. RESULTS: The well-known IRI marker genes (Kim1 and Lcn2) and novel hub genes (Hbegf, Serpine2, Apbb1ip, Trip13, Atf3, and Ncaph) had been proved by the quantitative real-time polymerase chain reaction (qRT-PCR). Thereafter, miRNAs targeted to the dysregulated genes were predicted and the miRNA-target network was constructed. Furthermore, the immune infiltration for these samples was predicted and the results showed that macrophages infiltrated to the injured kidney to affect the tissue repair or fibrosis. Hub genes were significantly positively or negatively correlated with the macrophage abundance indicating they played a crucial role in macrophage infiltration. CONCLUSIONS: Consequently, the pathways, hub genes, miRNAs, and the immune microenvironment may explain the mechanism of IRI and might be the potential targets for IRI treatments.

Developing and validating the model of tumor-infiltrating immune cell to predict survival in patients receiving radiation therapy for head and neck squamous cell carcinoma.

Background: Radiotherapy (RT) is a mainstay of head and neck squamous cell carcinoma (HNSCC) treatment. Due to the influence of RT on tumor cells and immune/stromal cells in microenvironment, some studies suggest that immunologic landscape could shape treatment response. To better predict the survival based on genomic data, we developed a prognostic model using tumor-infiltrating immune cell (TIIC) signature to predict survival in patients undergoing RT for HNSCC. Methods: Gene expression data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Data from HNSCC patients undergoing RT were extracted for analysis. TIICs prevalence in HNSCC patients was quantified by gene set variation analysis (GSVA) algorithm. TIICs and post-RT survival were analyzed using univariate Cox regression analysis and used to construct and validate a tumor-infiltrating cells score (TICS). Results: Five of 26 immune cells were significantly associated with HNSCC prognosis in the training cohort (all P<0.05). Kaplan-Meier (KM) survival curves showed that patients in the high TICS group had better survival outcomes (log-rank test, P<0.05). Univariate analyses demonstrated that the TICS had independent prognostic predictive ability for RT outcomes (P<0.05). Patients with high TICS scores showed significantly higher expression of immune-related genes. Functional pathway analyses further showed that the TICS was significantly related to immune-related biological process. Stratified analyses supported integrating TICS and tumor mutation burden (TMB) into individualized treatment planning, as an adjunct to classification by clinical stage and human papillomavirus (HPV) infection. Conclusions: The TICS model supports a personalized medicine approach to RT for HNSCC. Increased prevalence of TIIC within the tumor microenvironment (TME) confers a better prognosis for patients undergoing treatment for HNSCC.

Gene signatures in U-BIOPRED severe asthma for molecular phenotyping and precision medicine: time for clinical use.

INTRODUCTION: The use and generation of gene signatures have been established as a method to define molecular endotypes in complex diseases such as severe asthma. Bioinformatic approaches have now been applied to large omics datasets to define the various co-existing inflammatory and cellular functional pathways driving or characterizing a particular molecular endotype. AREAS COVERED: Molecular phenotypes and endotypes of Type 2 inflammatory pathways and also of non-Type 2 inflammatory pathways, such as IL-6 trans-signaling, IL-17 activation, and IL-22 activation, have been defined in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes dataset. There has also been the identification of the role of mast cell activation and of macrophage dysfunction in various phenotypes of severe asthma. EXPERT OPINION: Phenotyping on the basis of clinical treatable traits is not sufficient for understanding of mechanisms driving the disease in severe asthma. It is time to consider whether certain patients with severe asthma, such as those non-responsive to current therapies, including Type 2 biologics, would be better served using an approach of molecular endotyping using gene signatures for management purposes rather than the current sole reliance on blood eosinophil counts or exhaled nitric oxide measurements.

A polyamine metabolism risk signature for predicting the prognosis and immune therapeutic response of kidney cancer.

Background: Polyamine metabolism is critically involved in the proliferation and metastasis of tumor cells, including in kidney renal clear cell (KIRC) cancer. However, the molecular mechanisms underlying the effect of polyamines in KIRC cancer remain largely unknown. Methods: The messenger RNA (mRNA) expression profile of KIRC was downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ArrayExpress database. Differential expression analysis was performed with the "limma" package in R. Univariate Cox regression and multivariable Cox regression were used to estimate correlation between variables and prognosis. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to screen variables and construct a risk signature. A nomogram model was established using the risk signature and clinical variables. Receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA) were used to assess the predicted accuracy and clinical benefit of the model. Results: We identified nine differentially expressed polyamine metabolism-related genes (PMRGs) in TCGA-KIRC. Of these, six were closely associated with patients' outcomes. These six genes participated in different pathways and originated from different cell types within the tumor microenvironment (TME). Using the mRNA expression values of these genes, we constructed a 4-gene PMRG risk signature. Patients with high PMRG risk exhibited worse outcomes, and our analysis showed that the PMRG risk signature was an independent prognostic factor when clinical information was used as a covariate. We also found that multiple immune- or metabolism-related pathways were differentially enriched in high or low PMRG risk groups, suggesting that altering these pathways could lead to different clinical outcomes. Finally, in two external datasets, we found that the PMRG risk signature could predict the response of patients to immune therapy. Conclusions: In summary, our study identified several potentially important PMRGs in KIRC and constructed a practical risk signature, which could serve as a foundation for further development of polyamine metabolism-based targeted therapies for KIRC.

Whole-genome resequencing and transcriptome analyses of four generation mutants to reveal spur-type and skin-color related genes in apple (Malus domestica Borkh. Cv. Red delicious).

BACKGROUND: Bud sport is a kind of somatic mutation that usually occurred in apple. 'Red Delicious' is considered to be a special plant material of bud sport, whereas the genetic basis of plant mutants is still unknown. In this study, we used whole-genome resequencing and transcriptome sequencing to identify genes related to spur-type and skin-color in the 'Red Delicious' (G0) and its four generation mutants including 'Starking Red' (G1), 'Starkrimson' (G2), 'Campbell Redchief' (G3) and 'Vallee Spur' (G4). RESULTS: The number of single nucleotide polymorphisms (SNPs), insertions and deletions (InDels) and structural variations (SVs) were decreased in four generation mutants compared to G0, and the number of unique SNPs and InDels were over 9-fold and 4-fold higher in G1 versus (vs.) G2 and G2 vs. G3, respectively. Chromosomes 2, 5, 11 and 15 carried the most SNPs, InDels and SVs, while chromosomes 1 and 6 carried the least. Meanwhile, we identified 4,356 variation genes by whole-genome resequencing and transcriptome, and obtained 13 and 16 differentially expressed genes (DEGs) related to spur-type and skin-color by gene expression levels. Among them, DELLA and 4CL7 were the potential genes that regulate the difference of spur-type and skin-color characters, respectively. CONCLUSIONS: Our study identified potential genes associated with spur-type and skin-color differences in 'Red Delicious' and its four generation mutants, which provides a theoretical foundation for the mechanism of the apple bud sport.

A phospho-deficient α3 glycine receptor mutation alters synaptic glycine and GABA release in mouse spinal dorsal horn neurons.

Glycine receptors (GlyRs), together with GABAA receptors, mediate postsynaptic inhibition in most spinal cord and hindbrain neurons. In several CNS regions, GlyRs are also expressed in presynaptic terminals. Here, we analysed the effects of a phospho-deficient mutation (S346A) in GlyR α3 subunits on inhibitory synaptic transmission in superficial spinal dorsal horn neurons, where this subunit is abundantly expressed. Unexpectedly, we found that not only were the amplitudes of evoked glycinergic inhibitory postsynaptic currents (IPSCs) significantly larger in GlyRα3(S346A) mice than in mice expressing wild-type α3GlyRs (GlyRα3(WT) mice), but so were those of GABAergic IPSCs. Decreased frequencies of spontaneously occurring glycinergic and GABAergic miniature IPSCs (mIPSCs) with no accompanying change in mIPSC amplitudes suggested a change in presynaptic transmitter release. Paired-pulse experiments on glycinergic IPSCs revealed an increased paired-pulse ratio and a smaller coefficient of variation in GlyRα3(S346A) mice, which together indicate a reduction in transmitter release probability and an increase in the number of releasable vesicles. Paired-pulse ratios of GABAergic IPSCs recorded in the presence of strychnine were not different between genotypes, while the coefficient of variation was smaller in GlyRα3(S346A) mice, demonstrating that the decrease in release probability was readily reversible by GlyR blockade, while the difference in the size of the pool of releasable vesicles remained. Taken together, our results suggest that presynaptic α3 GlyRs regulate synaptic glycine and GABA release in superficial dorsal horn neurons, and that this effect is potentially regulated by their phosphorylation status. KEY POINTS: A serine-to-alanine point mutation was introduced into the glycine receptor α3 subunit of mice. This point mutation renders α3 glycine receptors resistant to protein kinase A mediated phosphorylation but has otherwise only small effects on receptor function. Patch-clamp recordings from neurons in mouse spinal cord slices revealed an unexpected increase in the amplitudes of both glycinergic and GABAergic evoked inhibitory postsynaptic currents (IPSCs). Miniature IPSCs, paired-pulse ratios and synaptic variation analyses indicate a change in synaptic glycine and GABA release. The results strongly suggest that α3 subunit-containing glycine receptors are expressed on presynaptic terminals of inhibitory dorsal horn neurons where they regulate transmitter release.

Identification and validation of risk score model based on gene set activity as a diagnostic biomarker for endometriosis.

Objective: The enigmatic nature of Endometriosis (EMS) pathogenesis necessitates investigating alterations in signaling pathway activity to enhance our comprehension of the disease's characteristics. Methods: Three published gene expression profiles (GSE11691, GSE25628, and GSE7305 datasets) were downloaded, and the "combat" algorithm was employed for batch correction, gene expression difference analysis, and pathway enrichment difference analysis. The protein-protein interaction (PPI) network was constructed to identify core genes, and the relative enrichment degree of gene sets was evaluated. The Lasso regression model identified candidate gene sets with diagnostic value, and a risk scoring diagnostic model was constructed for further validation on the GSE86534 and GSE5108 datasets. CIBERSORT was used to assess the composition of immune cells in EMS, and the correlation between EMS diagnostic value gene sets and immune cells was evaluated. Results: A total of 568 differentially expressed genes were identified between eutopic and ectopic endometrium, with 10 core genes in the PPI network associated with cell cycle regulation. Inflammation-related pathways, including cytokine-receptor signaling and chemokine signaling pathways, were significantly more active in ectopic endometrium compared to eutopic endometrium. Diagnostic gene sets for EMS, such as homologous recombination, base excision repair, DNA replication, P53 signaling pathway, adherens junction, and SNARE interactions in vesicular transport, were identified. The risk score's area under the curve (AUC) was 0.854, as indicated by the receiver operating characteristic (ROC) curve, and the risk score's diagnostic value was validated by the validation cohort. Immune cell infiltration analysis revealed correlations between the risk score and Macrophages M2, Plasma cells, resting NK cells, activated NK cells, and regulatory T cells. Conclusion: The risk scoring diagnostic model, based on pathway activity, demonstrates high diagnostic value and offers novel insights and strategies for the clinical diagnosis and treatment of Endometriosis.

Immune gene patterns and characterization of the tumor immune microenvironment associated with cancer immunotherapy efficacy.

Although immunotherapy has revolutionized cancer management, most patients do not derive benefits from it. Aiming to explore an appropriate strategy for immunotherapy efficacy prediction, we collected 6251 patients' transcriptome data from multicohort population and analyzed the data using a machine learning algorithm. In this study, we found that patients from three immune gene clusters had different overall survival when treated with immunotherapy (P < 0.001), and that these clusters had differential states of hypoxia scores and metabolism functions. The immune gene score showed good immunotherapy efficacy prediction (AUC was 0.737 at 20 months), which was well validated. The immune gene score, tumor mutation burden, and long non-coding RNA score were further combined to build a tumor immune microenvironment signature, which correlated more strongly with overall survival (AUC, 0.814 at 20 months) than when using a single variable. Thus, we recommend using the characterization of the tumor immune microenvironment associated with immunotherapy efficacy via a multi-omics analysis of cancer.

Antiplasmodial activity of the bulbs of Fritillaria cirrhosa D.Don (Syn: Fritillaria roylei Hook.): UPLC-IM-Q-TOF-MS/MS-based biochemometric approach for the identification of marker compounds.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria cirrhosa D.Don (Syn: Fritillaria roylei Hook.) (Hindi name: Kshirakakoli) is a critically endangered Himalayan medicinal plant, well documented in Ayurveda for its therapeutic uses against various disorders such as jvara (fever), kasa (respiratory tract disease) etc. Its bulbs are also used as Szechuan-Pei-Mu for their antipyretic properties in the traditional Chinese medicine. However, despite its ethnomedicinal usage, the therapeutic use of F. cirrhosa bulbs for jvara (fever) related conditions such as malaria has remained unexplored. Hence in the context of increasing global concerns about drug-resistant malaria, it is important to investigate the antiplasmodial activity of F. cirrhosa bulbs for novel antimalarial agents. AIM OF THE STUDY: To investigate the antiplasmodial effects of the extracts/fractions of F. cirrhosa bulbs by the biochemometric approach and to rationalize its ethnopharmacological usage for jvara (fever) related conditions such as malaria. MATERIAL AND METHODS: This study involves the UHPLC-MS-based plant material selection, preparation, quantification, and assessment of F. cirrhosa bulb extracts against CQ-sensitive Pf 3D7 & CQ-resistant Pf INDO strains. Further, UPLC-IM-Q-TOF-MS-based biochemometric approach has been applied for the identification of marker compounds responsible for the observed antiplasmodial effects. The identified marker compounds were also assessed for their in silico ADMET properties and binding efficacy with the drug transporter Pf CRT. RESULTS: Different F. cirrhosa bulb extracts/fractions showed promising antiplasmodial activity with IC50 values 2.71-19.77 µg/mL for CQ-resistant Pf INDO strain and 1.76-21.52 µg/mL for CQ-sensitive Pf 3D7 strain. UPLC-IM-Q-TOF-MS/MS-based biochemometric analysis revealed four marker compounds i.e., peimine (m/z 432.3448), peimisine (m/z 428.3504), puqiedinone (m/z 414.3379), and puqiedine (m/z 416.3509) responsible for the observed antiplasmodial activity. The identified marker compounds showed excellent binding efficacy with Pf CRT and suitable drug-like properties in silico. CONCLUSIONS: The study demonstrated promising antiplasmodial activity of the chloroform and alkaloid enriched fractions of F. cirrhosa bulbs and further identified the four marker compounds responsible for the promising antiplasmodial activity. These marker compounds i.e., peimine, peimisine, puqiedinone and puqiedine were identified by the biochemometric analysis as the putative antiplasmodial constituents of the F. cirrhosa bulbs. Further, in silico studies indicated the good binding affinity of the marker compounds with Pf CRT along with suitable ADMET properties. Overall, the study elucidates the antiplasmodial activity of F. cirrhosa bulbs from the western Himalayan region and provides nascent scientific evidence for their ethnopharmacological usage in jvara (fever) related conditions such as malaria.

IL1RAP expression and the enrichment of IL-33 activation signatures in severe neutrophilic asthma.

BACKGROUND: Interleukin (IL)-33 is an upstream regulator of type 2 (T2) eosinophilic inflammation and has been proposed as a key driver of some asthma phenotypes. OBJECTIVE: To derive gene signatures from in vitro studies of IL-33-stimulated cells and use these to determine IL-33-associated enrichment patterns in asthma. METHODS: Signatures downstream of IL-33 stimulation were derived from our in vitro study of human mast cells and from public datasets of in vitro stimulated human basophils, type 2 innate lymphoid cells (ILC2), regulatory T cells (Treg) and endothelial cells. Gene Set Variation Analysis (GSVA) was used to probe U-BIOPRED and ADEPT sputum transcriptomics to determine enrichment scores (ES) for each signature according to asthma severity, sputum granulocyte status and previously defined molecular phenotypes. RESULTS: IL-33-activated gene signatures were cell-specific with little gene overlap. Individual signatures, however, were associated with similar signalling pathways (TNF, NF-κB, IL-17 and JAK/STAT signalling) and immune cell differentiation pathways (Th17, Th1 and Th2 differentiation). ES for IL-33-activated gene signatures were significantly enriched in asthmatic sputum, particularly in patients with neutrophilic and mixed granulocytic phenotypes. IL-33 mRNA expression was not elevated in asthma whereas the expression of mRNA for IL1RL1, the IL-33 receptor, was up-regulated in the sputum of severe eosinophilic asthma. The mRNA expression for IL1RAP, the IL1RL1 co-receptor, was greatest in severe neutrophilic and mixed granulocytic asthma. CONCLUSIONS: IL-33-activated gene signatures are elevated in neutrophilic and mixed granulocytic asthma corresponding with IL1RAP co-receptor expression. This suggests incorporating T2-low asthma in anti-IL-33 trials.

The Swiss health care atlas-relaunch in scale.

Inspired by the Dartmouth Atlas of Health Care, an early version of the Swiss Atlas of Health Care (SAHC) was released in 2017. The SAHC provides an intuitive visualization of regional variations of medical care delivery and thus allows for a broad diffusion of the contents. That is why the SAHC became widely accepted amongst health care stakeholders. In 2021, the relaunch of the SAHC was initiated to update as well as significantly expand the scope of measures depicted on the platform, also integrating indicators for outpatient care in order to better reflect the linkages between inpatient and outpatient health care provision. In the course of this relaunch, the statistical and technical aspects of the SAHC have been reviewed and updated. This paper presents the key aspects of the relaunch project and provides helpful insights for similar endeavors elsewhere.

Effects of Covid-19 on the elective surgery: an approach based on the case of the Italian Province of Bolzano.

BACKGROUND: As of February 2020, the rise of COVID-19 cases led to significant pressures in the Northern parts of Italy, including the province of Bolzano (a small territorial reality on the border between Italy and Austria), and left the Italian National Health System (NHS) unprepared for the initial wave of the SARS-CoV-2 pandemic. OBJECTIVE/METHODS: By dividing the analyses into two phases, the study assesses the effect of COVID-19 for the years 2018-2019 and 2020-2021. The first phase highlights the hospitalization rates in the Province of Bolzano in comparison to other Italian regions. In the second step, the Systematic Component of Variation (SCV) has been applied to calculate the differences between the admission rates for the elective surgery (tonsillectomy, vein stripping, hip replacement, knee replacement, and arthroscopy) in the four health districts (HDs) of the Province of Bolzano. RESULTS: Overall, the findings demonstrate that the effect of COVID-19 cases has resulted in a 20% reduction in hospitalization rates. A variation of less than 30% for knee and hip replacements and up to 75% for vein stripping is seen for elective surgeries. According to the SCV values for each elective procedure, the results indicate comparable levels of variation across the two time periods, with tonsillectomy showing the lowest levels of variation, arthroscopy and vein stripping having the highest levels, hip replacement having a high level and knee replacement having a low-medium level. CONCLUSIONS: The data show no significant changes in the variation between the four HDs in the province of Bolzano, suggesting that the COVID-19 cases have a proportionate impact on hospitalization rates.