This study explores fault-tolerant consensus in leader-following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler-Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Cytologic diagnosis of extra‐adrenal paraganglioma presenting as a peripancreatic mass is challenging with a high rate of diagnostic error. We present a case of a peripancreatic mass identified by radiology as a gastrointestinal stromal tumor. Endoscopic ultrasound‐guided fine needle aspiration (FNA) of the mass showed a moderately cellular tumor composed of small to medium sized neoplastic cells with round to oval nuclei arranged singly and in loose clusters. The cells were positive for neuroendocrine markers (synaptophysin and chromogranin) and negative for CD117. A diagnosis of a neoplasm with a neuroendocrine tumor (NET) was made on FNA cytology. The subsequent surgical resection of the tumor revealed peripancreatic paraganglioma with immunohistochemistry positive for synaptophysin, chromogranin, and S100. The latter delineates the sustentacular cells. Although paraganglioma is a well recognized tumor, a detailed comparison of peripancreatic paraganglioma versus pancreatic/gastrointestinal NET is still lacking.

EUS–TA in unresectable pancreatic cancer requires not only a tissue diagnosis but also tissue collection in anticipation of comprehensive genomic profiling. However, the optimal puncture target remains controversial. Therefore, the Primary and Metastatic Lesions in Pancreatic Cancer (PRIMATE) study was designed to clarify the optimal target by comparing the success rates for meeting OncoGuide NCC Oncopanel (NOP) analysis criteria on pre-check primary and metastatic lesion specimens obtained during the same EUS–TA session in patients with invasive pancreatic ductal adenocarcinoma. In this ongoing prospective study, two specimens, each from primary and metastatic lesions, are obtained by EUS–TA (typically using a 19G fine-needle biopsy needle) in patients with invasive pancreatic ductal adenocarcinoma. The primary endpoint is the proportion of EUS–TA specimens that meet NOP analysis criteria during pre-check (i.e., tumor cellularity ≥ 20% and tissue area ≥ 4 mm2), which are then compared between primary and metastatic lesions. This study has been approved by the National Cancer Center Institutional Review Board (Research No. 2022-168). The results of this study will be reported at an international conference and published in an international peer-reviewed journal. The trial registration number is UMIN 000048966.

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track response to therapy, and parse causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson’s disease (PD).

Gene regulation is vital for cellular function and homeostasis, involving diverse mechanisms controlling specific gene products and contributing to tissue-specific gene expression. Dysregulation leads to diseases, emphasizing the need for understanding these mechanisms. Non-coding regions, notably enhancers and super-enhancers (SEs), act as crucial gene regulators, orchestrating transcriptional activity via transcription factors (TFs). SEs, with high activity, are pivotal in cell identity and disease progression. Current computational approaches focus on individual regulators like TFs and miRNAs, neglecting SE interactions. We emphasize incorporating SEs into models to enhance understanding. Experimental studies have recently linked miRNAs and TFs to SEs. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) provides valuable SE information. In this review, we categorize computational methods leveraging TF and miRNA data into three areas and explore challenges integrating enhancers/SEs. These include unraveling indirect regulatory networks, identifying network motifs, and enriching pathway identification by dissecting gene regulators, including SEs. We hypothesize that addressing these challenges will enhance our understanding of gene regulation, aiding in identifying therapeutic targets and disease biomarkers. We believe that understanding the role of ChIP-Seq data in predicting the effect of miRNA on gene regulation is crucial to construct statistical/computational model that would tackle these challenges.

Background: Colorectal cancer (CRC) patients experienced multiple chemotoxicity affecting treatment compliance, survival, and quality of life (QOL). Prior research shows clinician-reported chemotoxicity (i.e., grading scales or diagnostic codes) predicts rehospitalization and cancer survival. However, a comprehensive synthesis of clinician-reported chemotoxicity is still lacking. Objectives: We conducted a systematic review and meta-analysis to determine the chemotoxicity's prevalence and risk factors in CRC. Methods: A systematic search from 2009 to 2024 yielded 30 studies for review, with 25 included in the meta-analysis. Results: Pooled prevalences of overall, non-hematological, and hematological moderate-to-severe toxicities were 45.7%, 39.2%, and 25.3%, respectively. The most common clinician-reported chemotoxicities were gastrointestinal (GI) toxicity (22.9%) and neuropathy or neutropenia (17.9%). Significant risk factors at baseline were malnutritional status, frailty, impaired immune or hepato-renal functions, short telomere lengths, low gut lactobacillus levels, age, female sex, aggressive chemotherapy, and low QOL. Age was associated with neutropenia (β: -1.44) and GI toxicity (β:1.85) (Ps 65 y.o.) had higher prevalences of overall (OR: 1.14) and GI (OR: 1.65) toxicities, but a lower prevalence of neutropenia (OR: 0.65) than younger adults (Ps

Introduction: Gastric cancer (GC) is one of the most frequently diagnosed cancers in the world. Although the incidence is decreasing in developed countries, treatment results are still unsatisfactory. The standard treatment for locally advanced gastric cancer (LAGC) is gastrectomy with perioperative chemotherapy. Aim: Assessment of selected microRNAs (miRNAs) in chemoresistance in archival material from LAGC. Material and method: The research group consisted of archival material from 10 patients with LAGC. Histological material from each patient was used from a biopsy performed during gastroscopy and after surgery preceded by 4 cycles of neoadjuvant chemotherapy (NAC) according to the FLOT or FLO regimen. The expression of selected miRNAs was assessed in the tissue material, such as miRNA-21-3p, miRNA-21-5p, miRNA-106a-5p, miRNA-122-3p, miRNA-122-5p, miRNA-143-3p, miRNA-143-5p, miRNA-203a-3p, miRNA-203-5p, miRNA-551b-3p, miRNA-551b-5p and miRNA-574-3p. miRNA expression was assessed by quantitative chain reaction polymerase reverse transcriptase (qRT-PCR). The response to NAC was assessed by computed tomography of the abdomen, chest and histopathology after gastrectomy. The statistical analyses were performed using GraphPad Prism 9.The significance limit was set at p

Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets. Using proteogenomic analyses of primary EOC tumors, we previously identified 91 aberrantly expressed tumor-specific antigens (TSAs) originating from unmutated genomic sequences. Most of these TSAs derive from non-exonic regions, and their expression results from cancer-specific epigenetic changes. The present study aimed to evaluate the immunogenicity of 48 TSAs selected according to two criteria: presentation by highly prevalent HLA allotypes and expression in a significant fraction of EOC tumors. Using targeted mass spectrometry analyses, we found that pulsing with synthetic TSA peptides leads to a high-level presentation on dendritic cells. TSA abundance correlated with the predicted binding affinity to the HLA allotype. We stimulated naïve CD8 T cells from healthy blood donors with TSA-pulsed dendritic cells and assessed their expansion with two assays: MHC-peptide tetramer staining and TCR Vβ CDR3 sequencing. We report that these TSAs can expand sizeable populations of CD8 T cells and, therefore, represent attractive targets for EOC immunotherapy.

Bladder cancer (BC) is one of the most lethal genitourinary malignancies owing to its propensity for recurrence and poor survival. The biochemical pathway, signal transducer and activator of transcription 3 (STAT3), has gained significance as a molecular pathway that promotes proliferation, invasion, and chemoresistance. In this study, we explored the targeting of STAT3 with TTI-101 and SH5-07 in bladder cancer (BCa) and elucidated the mechanisms in three-dimensional (3D) spheroid and tumoroid models. We optimized the growth of spheroids from human, rat, and mouse BCa cell lines (J82, NBT-II, and MB49, respectively), and tumoroids from BBN (N-butyl-N-(4-hydroxybutyl)-nitrosamine) induced rat bladder tumors. Cell viability was assessed using MTT and trypan blue assays. ATP production, ROS production, and calcium AM (CA)/EtBr staining were used to measure the spheroid and organoid inhibition and mitochondrial function. Western blot analysis was performed to evaluate the pharmacodynamic markers involved in cell proliferation, apoptosis, cancer stem cells (CSCs), and STAT3 signaling in BCa. We found that targeting STAT3 (using TTI-101 and SH5-07) significantly reduced the proliferation of BCa spheroids, and tumoroids, which was accompanied by decreased expression of pSTAT3, Cyclin D1, and PCNA. Our data also demonstrated that treatment with STAT3 inhibitors induced ROS production and cell death in BCa spheroids and organoids. STAT3 inhibition induced cell death was associated with the activation of caspase 3/7 and PARP cleavage. Moreover, TTI-101 and SH5-07 targets cancer stem cells by downregulating the expression of CD44 and CD133 in 3D models. This study provides the first evidence for the prevention of bladder cancer with small-molecule inhibitors TTI101 and SH5-07 via suppression of CSCs and STAT3 signaling.

During HIV-1 virus assembly the genomic RNA (vRNA) is selected for packaging by the viral protein Gag because it contains a specific packaging signal, Psi. While there have been numerous studies of Gag-Psi interactions, there is almost no information on kinetic aspects of this interaction. We have investigated the kinetics of Gag binding to different RNAs using switchSENSE DRX2 technology. We measured the association rate of Gag binding to monomeric Psi, to a “Multiple Binding Site Mutant” Psi that is inactive for genome packaging in vivo, and to a scrambled Psi. We discovered that Gag binds more rapidly to Psi RNA than to the mutant or scrambled RNAs. Furthermore, rapid Gag association kinetics are retained within sub-regions of Psi: Gag associates more rapidly with RNA containing only the 3’ two of the three Psi stem-loops than with monomeric RNA containing the 5’ two stem-loops or a scrambled RNA. No differences were detectable with individual Psi stem-loops. Interestingly, the rate of binding of Gag molecules to Psi increases with increasing Gag concentration, suggesting cooperativity in binding. The results are consistent with the hypothesis that selectivity in packaging derives from kinetic differences in initiation of particle assembly.

Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at screening could save more lives. This mammography re-view paper provides a systematic review of computer-aided techniques during a specific time frame for the segmentation and classification of microcalcification, evaluating image processing, machine learning, and deep learning techniques. The systematic review is meticulously carried out, adhering closely to the preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This article focuses on mammographic breast cancer detection approaches based on automated systems, discussed chronologically from 1970 through 2023. This article encompasses the breadth of artificial intelligence-based methods from the most primitive to the most sophisticated models. Image processing and machine learning-based methods are compre-hensively reviewed. The evaluation of a deep learning architecture based on self-extracted features for classification tasks demonstrated outclass performance. Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. This research work is aligned with the United Nations' sustainability de-velopment goals.

Gastric cancer is the 5th most common disease in the world and the 4th most common cause of death. It is diagnosed through esophagogastroduodenoscopy with biopsy, however there are limitations in finding lesions in the early stages. Recently, research has been actively conducted to use liquid biopsy to diagnose various cancers, including gastric cancer. Various substances derived from cancer are reflected in the blood. By analyzing these substances, it was expected that not only the presence or absence of cancer but also the type of cancer can be diagnosed. However, the amount of these substances is extremely small, and even these have various variables depending on the characteristics of the individual or the characteristics of the cancer. To overcome these, we collected methylated DNA fragments using MeDIP and compared them with normal plasma to characterize gastric cancer tissue or patient’s plasma. And we attempted to diagnose gastric cancer using the characteristics of cancer reflected in the blood through the cancer tissue and patient’s plasma. As a result, we confirmed that the consistency of common methylated fragments between tissue and plasma was approximately 41.2%, and found the possibility of diagnosing and characterizing cancer using the characteristics of the fragments through SFR and 5'end-motif analysis.

The p53 tumor suppressor protein shows antiviral activity. The replication of viruses is also antagonized by interferons (IFNs) – cytokines, which control immunity genes by the STAT transcription factors. The best studied interferons belong to type I (e.g. IFNα) and type II (IFNγ) groups. IFNα and IFNγ both induce activating phosphorylation of STAT1 on Tyr701. Previously, we noticed that p53 activates SOCS1, which is a negative regulator of STAT1 phosphorylation. Thus, we hypothesized that p53 by activating SOCS1 expression reduces phosphorylation of STAT1 and attenuates activation of genes stimulated either by IFNα or IFNγ. To test this hypothesis, we exposed p53-proficient and p53-deficient cells to strong p53 activators, and either to IFNα or IFNγ. Subsequently, we estimated the phosphorylation status of STAT1 and the expression of genes regulated by either of these cytokines. Strong activation of p53 reduced the phosphorylation of STAT1 on Tyr701, however surprisingly it did not lead to reduced expression of most tested interferon-stimulated genes. On contrary, p53 and IFNγ synergized in the activation of CASP1, IFIT1 and IFIT3 genes. We conclude that the interactions between p53 and interferon-activated pathways are more complicated than initially expected, but the apparent cooperation between p53 and IFNγ deserves further studies.

From their discovery in 2002, BRAF mutations have been identified as clear drivers of oncogenesis in several cancer types. Currently, their incidence rate is nearly 7% of all solid tumors with BRAF V600E constituting approximately 90% of these diagnoses [1]. In melanoma, thyroid cancer, and histiocytic neoplasms, BRAF hotspot mutations are found at a rate of about 50%, while in lung and colorectal cancers they range from 3 to 10% of reported cases [2-5]. Though present in other malignancies such as breast and ovarian cancers, they constitute a small portion of diagnoses (<1%). Given their frequency along with advancements in screening technologies, various methods are used for the detection of BRAF-mutant cancers. Among these are targeted next-generation sequencing (NGS) on tumor tissue or circulating tumor DNA (ctDNA) and immunohistochemistry (IHC)-based assays. With advancements in detection technologies, several approaches have been taken for the treatment of BRAF mutant cancers. In this review we retrace the milestones that led to the clinical development of targeted therapies currently available for these tumors.

Cancer treatment is a significant focus in medicine owing to the increasing global incidence. Patients with advanced cancers that do not respond to conventional therapies have limited options and an unfavorable prognosis. Consequently, researchers are investigating complementary approaches to conventional treatments. One such approach is alkalization therapy, which aims to neutralize the acidic tumor microenvironment (TME) by increasing its pH level. The acidic TME promotes inflammation, tumor progression, and drug resistance. Alkalization therapy has been demonstrated to be effective for various cancers. In addition, natural products, such as triterpenoids, parthenolides, fulvic acid, Taxus yunnanensis, and apple pectin have the potential to alleviate symptoms, maintain physical fitness, and improve treatment outcomes of cancer patients through their anti-inflammatory, antioxidant, and anticancer properties. In this review, we focus on the effects of alkalization therapy and natural products on cancer. Furthermore, we present a case series of advanced cancer patients who received alkalization therapy and natural products alongside standard treatments, resulting in long-term survival. We posit that alkalization therapy together with the supplementation of natural products may confer benefits to cancer patients by mitigating the side effects of chemotherapy and complementing standard treatments. However, further research is warranted to validate these clinical findings.

For monitoring of chimeric antigen receptor (CAR) T-cell therapies antigen-based CAR detection methods are usually applied. However, for each target-antigen a separate detection system is required. Furthermore, when monitoring CAR T-cells in the blood of patients treated with bispecific antibodies or T-cell engagers (bsAbs/BiTEs) recognize the same antigen, these methods producing false-positive results in clinical diagnostics. Anti-CAR-linker monoclonal antibodies (mAbs) targeting the linker sequence between the variable domains of the antigen binding CAR fragment, promise an universal and unbiased CAR detection. To test this, we analyzed clinical specimens of all BCMA- and CD19 targeting CAR T-cell products currently approved for clinical use. We found a highly specific and sensitive CAR detection by using anti-CAR-linker mAb in blood cells from patients treated with Ide-cel, Tisa-cel, Axi-cel, Brexu-cel, and Liso-cel. For Ide-cel and Tisa-cel the sensitivity was significant lower compared to antigen-based CAR detection assays. Strikingly, the specificity of anti-CAR linker mAb was not affected by the simultaneous presence of bispecific blinatumomab or teclistamab for Axi-cel, Brexu-cel, Liso-cel or Ide-cel, respectively. Cilta-cel (containing an monomeric G4S-CAR linker) could not be detected by anti-CAR linker mAb. In conclusion, anti-CAR-linker mAbs are highly specific and useful for CAR T-cell monitoring but not universal applicable.

Tertiary lymphoid structures (TLSs) have become the focus of antitumor immunity. However, the prognostic significance of TLSs in epithelial ovarian cancer (EOC) treated with primary debulking surgery (PDS) or interval debulking surgery (IDS) remains unelucidated. This retrospective study examined the prognostic value of TLSs in tumor tissues obtained during PDS and IDS. Pathological specimens were collected from patients with EOC who underwent PDS or IDS between 2017 and 2020 at the National Cancer Center Hospital East. The correlation of tumor-infiltrating lymphocyte frequency, TLS presence, and PD-L1 expression with progression-free survival (PFS) and overall survival (OS) and the correlation between TLS and PD-L1 expression were analyzed. Overall, 25 specimens (15 from PDS and 10 from IDS) were analyzed. The presence of TLS was associated with a significantly longer OS in patients who underwent PDS but not in patients who underwent IDS. No correlation was identified between TLS and PFS in patients with PDS or with IDS. However, TLS was positively correlated with PD-L1 positivity. The prognostic impact of TLS, specifically in pre-chemotherapy specimens, and a positive correlation between TLS and PD-L1 indicate the potential of TLS as a meaningful biomarker for understanding antitumor immunity and developing immunotherapy for EOC.

Pancreatic neuroendocrine neoplasms (pNENs) are rare tumors accounting for only 1-2% of all pancreatic tumors. pNENs are pathologically heterogeneous and are categorized into three groups (neuroendocrine tumor: NET G1, NET G2 and neuroendocrine carcinoma: NEC) on the basis of Ki-67 proliferation index and mitotic count according to the 2010 WHO classification of gastroenteropancreatic NENs. NEC in this classification includes both histologically well-differentiated and poorly differentiated subtypes, and modification of the WHO 2010 classification is under discussion based on genetic and clinical data. Genomic analysis has revealed NETs G1/G2 have genetic alterations in chromatin remodeling genes such as MEN1, DAXX and ATRX, whereas NECs have an inactivation of TP53 and RB1, and these data suggest that different treatment approaches would be required for NET G1/G2 and NEC. While there are promising molecular targeted drugs, such as everolimus or sunitinib, for advanced NET G1/G2, treatment stratification based on appropriate predictive and prognostic biomarkers is becoming an important issue. The clinical outcome of NEC is still dismal, and a more detailed understanding of the genetic backround together with preclinical studies to develop new agents, including those already under investigation for SCLC, will be needed to improve the prognosis.

We conducted a retrospective evaluation of the clinical outcomes and prognostic factors in patients with non-metastatic castration-resistant prostate cancer (nmCRPC) treated with first-line androgen receptor signaling inhibitors (ARSI) in real-world clinical practice in Japan. Between 2012 and 2023, a total of 127 consecutive patients with nmCRPC received ARSI treatment. Overall survival (OS), metastatic-free survival (MFS), and prostate-specific antigen progression–free survival (PSA-PFS) from ARSI initiation were assessed using Kaplan–Meier methodology. Clinical factors associated with OS in nmCRPC were analyzed using the Cox proportional hazards model. Among the patients, 72, 26, 12, and 17 received enzalutamide (ENZ), abiraterone (ABI), apalutamide (APA), and darolutamide (DARO) as first-line therapy. The median OS and MFS for all patients were 79.0 and 42.0 months, respectively. Median PSA-PFS was 27.0, 20.0, 10.0, and 14.0 months for patients treated with ENZ, ABI, APA, and DARO, respectively (p = 0.33). Multivariate analysis revealed that a baseline PSA level ≥3.67 ng/ml at ARSI initiation was significantly associated with poorer OS (p = 0.002). ARSI demonstrated favorable efficacy in nmCRPC patients. There were no significant differences in clinical outcomes among different types of ARSI therapy for nmCRP. Elevated baseline PSA at ARSI initiation was significantly associated with poorer OS.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

The p53 tumor suppressor protein is an activator of transcription. Diverse stress factors lead to various sets of posttranslational modifications of p53 what results in different sets of upregulat-ed genes. We noticed that actinomycin D and nutlin-3a (A+N) synergize in inducing activating phosphorylations of p53 and upregulation of selected p53-target genes. Here we found that one of these genes is DUSP13, which codes for poorly-studied, dual-specificity phosphatase having at least two isoforms, one expressed in testis and the other in skeletal muscles. In cancer cells ex-posed to A+N, DUSP13 is expressed from an alternative promoter in intron, what results in ex-pression of isoform named TMDP-L1. The luciferase reporter tests demonstrated that this pro-moter is activated by both endogenous and ectopically expressed p53. We showed for the first time that mRNA expressed from this promoter actually produces the protein, which can be de-tected by Western blotting in all examined cancer cell lines with wild-type p53 exposed to A+N. In some cell lines it is also induced by clinically relevant camptothecin or by nutlin-3a acting alone. This isoform, fused with green fluorescent protein localizes in perinuclear region of cells. Thus, TMDP-L1 isoform may be an important element of p53-regulated stress response system.

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curable for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists or/and to downstage patients who are beyond Milan criteria are widely utilized. We conducted a literature-based review to evaluate the role of systemic therapies as a bridging treatment to liver transplantation (LT) in HCC patients. Tyrosine Kinase Inhibitors (TKIs) can be used as a bridging systemic therapy to LT in patients with contraindication to locoregional liver-directed therapies. Immune Checkpoint Inhibitors (ICIs) treatment can be utilized either as a monotherapy or as a combination therapy with Bevacizumab or TKIs prior to LT. Acute rejection post liver transplantation is a concern in the context of ICIs treatment. Thus, a safe ICI washout period before LT and cautious post-LT immunosuppression strategies are required to reduce post-LT rejections and to optimize clinical outcomes. Nevertheless, prospective clinical trials are needed to establish definitive conclusions about the utility of systemic therapy as a bridging modality prior to LT in HCC patients.

Cellular senescence accumulates with age and has been shown to impact numerous physiological and pathological processes, including immune function. The role of cellular senescence in cancer is multifaceted, but the impact on immune checkpoint inhibitor response and toxicity has not been fully evaluated. In this review, we evaluate the impact of cellular senescence in various biological compartments, including the tumor, the tumor microenvironment, and the immune system on immune checkpoint inhibitor efficacy and toxicity. We provide an overview of the impact of cellular senescence in normal and pathological contexts and examine recent studies that have connected aging and cellular senescence to immune checkpoint inhibitor treatment in both the pre-clinical and clinical contexts. Overall, senescence plays a multi-faceted, context-specific role, and has been shown to modulate immune-related adverse event incidence as well as immune checkpoint inhibitor response.

1) Background: When women receive a diagnosis of a gynecologic malignancy, they can have questions about their diagnosis or treatment that can result in voice queries to virtual assistants. Recent advancement in artificial intelligence (AI) has transformed the landscape of medical information accessibility. The Google virtual assistant (VA) outperformed Siri, Alexa, and Cortana in voice queries presented prior to the explosive implementation of AI in early 2023. The efforts presented here focus on determining if advances in AI in the last 12 months improved the accuracy of Google VA responses related to gynecologic oncology. (2) Methods: Previous questions were utilized to form a common basis for queries prior to 2023 and responses in 2024. Correct answers were obtained from the UpToDate medical resource. Responses related to gynecologic oncology were obtained using Google VA, as well as the generative AI chatbots Google Bard/Gemini and Microsoft Bing-Copilot. (3) Results: The AI narrative responses varied in length and positioning of answers within the response. Google Bard/Gemini achieved an 87.5% accuracy rate, while Microsoft Bing-Copilot reached 83.3%. In contrast, the Google VA’s accuracy in audible responses improved from 18% prior to 2023 to 63% in 2024. (4) Conclusion: While the accuracy of the Google VA has improved in the last year, it underperformed Google Bard/Gemini and Microsoft Bing-Copilot so that there is considerable room for further improved accuracy.

Background: In high-risk breast cancer patients with skin infiltration the administration of a uniform dose to superficial tissues is fundamental in order to reduce local skin relapse. A personalized bolus may prevent the potential standard bolus’ inadequate dose distribution due to air gaps between the bolus and the skin. In this pilot study, we introduced in clinical practice the use of a personalized 3D printed bolus filled with ultrasound transmission gel. Methods: Seven patients undergoing radiotherapy after mastectomy were selected. 3D printed bolus dosimetric assessment was performed with MOSFET dosimeters on an anthropomorphic phantom and subsequently on three selected cases with increasing bolus shape irregularity. Acute/late toxicity and local control was assessed. Results: Overall, for the clinical cases the percentage median difference between measured and calculated doses was -2.7% (-7.0%÷4.9%). Median follow-up was 21 months. After two years, one patient showed G2 pain, one patient manifested G1 telangiectasia, one patient showed G1 hyperpigmentation, and two patients had no relevant toxicity. Conclusions: Personalized 3D-printed bolus filled with ultrasound gel may easily reproduce the standard bolus’ consistency providing an accurate coverage of the target area with tolerable acute/late toxicity grades. This is a pilot study and further investigations are needed.

Expression of miR-21 has been found to be altered in almost all types of cancers and it has been classified as an oncogenic microRNA. In addition, expression of tumor suppressor gene RECK is associated with miR-21 overexpression in high-grade cervical lesions. In the present study we analyze the role of miR-21 in RECK gene regulation in cervical cancer cells. To identify the downstream cellular target genes of upstream miR-21, we silenced endogenous miR-21 expression using siRNAs. We analyzed the expression of miR-21 and RECK, as well as functional effects on cell proliferation and migration. We found that in cervical cancer cells there was an inverse correlation between miR-21 expression and RECK mRNA and protein expression. SiRNAs to miR-21 increased luciferase reporter activity in construct plasmids containing the RECK-3′-UTR microRNA response elements MRE21-1, MRE21-2, and MRE21-3. The role of miR-21 in cell proliferation was also analyzed and cancer cells transfected with siRNAs exhibited a markedly reduced cell proliferation and migration. Our findings indicate that miR-21 post-transcriptionally down-regulates the expression of RECK to promote cell proliferation and cell migration inhibition in cervical cancer cell survival. Therefore, miR-21 and RECK may be potential therapeutic targets in gene therapy for cervical cancer.

Acinar cell carcinoma (ACC) accounts for about 1% of pancreatic cancers. The molecular and clinical features of ACC are less characterized than pancreatic ductal adenocarcinoma. We retrospectively evaluated the clinical and molecular features of ACC patients who underwent germline and/or somatic molecular testing at The University of Texas MD Anderson Cancer Center from 2008 to 2022. Patient information was extracted from our institutional database with the approval of Institutional Review Board. We identified 16 patients with available molecular testing results. Fourteen patients had metastatic disease, 1 had borderline resectable disease, and 1 had localized resectable disease at diagnosis. Fifteen patients were wild type for KRAS (1 patient had unknown KRAS status). Somatic/germline mutations of DNA damage repair genes (BRCA1/2, PALB2, and ATM) were present in 5 of 12 patients tested for these genes. One patient was found to have RET fusion and responded favorably to selpercatinib for over 42 months. The median overall survival (OS) was 24 months for patients with metastatic disease. One of the additional two cases which had BostonGene tests was found to have NTRK1 fusion. RNA and TME analysis by BostonGene of the two cases reported immune desert features and relatively lower RNA levels of CEACAM5, CD47, CD74 and MMP1 and higher CDH6 compared with PDAC.

Accurate prostate volume estimation is crucial for effective prostate disease management. Ultrasound (US) imaging, particularly transrectal ultrasound, offers a cost-effective and rapid assessment. However, US images often suffer from artifacts and poor contrast, making prostate volume estimation challenging. This review explores recent advancements in deep learning (DL) techniques for automatic prostate segmentation in US images as a primary step for prostate volume estimation. We examine various DL architectures, including traditional U-Net modifications and innovative designs incorporating residual connections, multi-directional image data, and attention mechanisms. Additionally, we discuss pre-processing methods to enhance image quality, the integration of shape information, and strategies to improve the consistency and robustness of DL models. The effectiveness of these techniques is evaluated through metrics such as Dice Similarity Coefficient, Jaccard Index, and Hausdorff Distance. The review highlights the potential of DL in improving prostate volume estimation accuracy and reducing clinical workload, while also identifying areas for future research to enhance model performance and generalizability.

Background: Ovarian mesonephric-like adenocarcinoma (MLA) is a newly described histological type known for its aggressive behavior. This study aims to determine the frequency of ovarian MLA, review existing literature, and elucidate its clinicopathological characteristics, including potential therapeutic targets. Methods: We retrospectively reviewed the pathological diagnoses of 516 primary ovarian cancer surgical cases at our institution from 2010 to 2023. MLAs exhibiting typical morphological and immunohistochemical features were included. The frequency and clinicopathological characteristics of these cases were summarized. Additionally, we conducted a literature search using PubMed to collect and summarize previously reported cases of ovarian MLA. Results: Among the 516 primary ovarian cancer cases, we identified 3 cases (0.6%) of MLA. The patients were 52-76 years old, and the initial FIGO stages were IC1 (2 cases) and IIIB (1 case). All cases exhibited HRP, pMMR, PD-L1 negativity (CPS&lt;1), and HER2-low expression. Two cases experienced metastatic recurrence. A literature review identified 97 cases of MLA. MLA frequently exhibited KRAS mutations (90%, 38/42), with a recurrence rate of 39% (26/67). Conclusion: MLA accounted for 0.6% of malignant ovarian tumors at our institution, all of which were advanced or recurrent cases. These cases showed HRP, pMMR, and PD-L1 negativity, indicating a lack of current therapeutic targets. Literature also reports a high incidence of advanced and recurrent cases, highlighting the need for accurate diagnosis and the development of new treatments. The frequent KRAS mutations suggest a potential therapeutic target for recurrent or metastatic MLA.

First-line treatment for advanced large-cell neuroendocrine carcinoma of the lung (LCNEC) has limited efficacy. This study aimed to explore the efficacy and safety of everolimus combined with EP regimen chemotherapy (etoposide + cisplatin, EP) in the first-line treatment for LCNEC. The patients were randomly assigned to the experimental or control group, with 20 patients in each group. The experimental group received the mTOR inhibitor everolimus 5 mg once a day combined with EP ivgtt, d1-3, every 3 weeks for 4–6 cycles. The control group received EP only and the infusion method was the same as that of the experimental group. The safety in the experimental group was controllable and not inferior to that in the control group. Serious adverse effects were observed in approximately 10% of patients. Objective response rate (ORR) for the experimental and control groups were 15% vs. 0 (P=0.231), disease control rate (DCR) was 100% vs. 32% (P

During recent years there is an on-going deployment of 5G base stations for radiofrequency (RF) communication in Sweden as well in many other countries. This is made without investigations on risks to human health and the environment. Since 2016 we have made several measurements of environmental exposure to RF radiation in Stockholm, Sweden, including previous generations and now also 5G. In the current study, performed in October 2023, the broadband meter Narda-550 with the probe EF-1891 was used. It gives results in the root mean square (RMS) mode, thus not peak levels. Both the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the US Federal Communications Commission (FCC) base their guidelines on RMS levels of RF radiation. Measurements were made in similar city areas as in our previous studies. Results show that the RF radiation has increased substantially. High maximum levels were found at e.g. the Central Railway Station (3 637 191 µW/m2), and popular walking streets such as Mäster Samuelsgatan (11 613 976 µW/m2), and Drottninggatan (5 271 555 µW/m2). The peak values would be much higher. These levels are in the same magnitude or even higher than those measured in homes of persons that rapidly developed symptoms of the microwave syndrome after installation of 5G, usually in combination with 4G+, in the neighborhood. They are also substantially higher than levels that have previously been linked to cancer and the microwave syndrome in studies of people living near base stations and masts from previous generations of telecommunications.

This study evaluated the presence of Human Papillomavirus (HPV) and Bovine Leukemia Virus (BLV) DNA in breast cancer (BC) samples from women in Northeastern Brazil. We analyzed 186 formalin-fixed, paraffin-embedded tissue block samples using PCR and qPCR to detect HPV and BLV DNA. BLV DNA was not detected in any BC patients. However, HPV DNA was found in 46.2\% of the BC samples: 44.6\% were positive for HPV16, 3.5\% for HPV31, and 2\% were coinfected with HPV16 and HPV31. Additionally, we found an association between HPV-positive BC and Ki-67 expression (P=0.03, OR=1.85; CI=1.02-3.34), as well as between HPV31-positive BC and mitotic index (P=0.047). Although BLV was not detected in BC patients from Northeastern Brazil, the association between HPV and cell proliferation markers warrants further investigation, as HPV may contribute to the aggressiveness of BC in these patients.

: Optical coherence tomography is a non-invasive imaging technique that provides three-dimensional visualization of subsurface tissue structures. OCT has been proposed and explored in literature as a tool to assess oral cancer status, select biopsy sites, or identify surgical margins. Our endoscopic OCT device can generate widefield (centimeters long) imaging of lesions at any location in the oral cavity – but it is challenging for raters to quantitatively assess and score large volumes of data. Leveraging a previously developed epithelial segmentation network, this work develops quantifiable biomarkers that provide direct measurements of tissue properties in three-dimensions. We hypothesize that features related to morphology, tissue attenuation, and contrast between tissue layers will be able to provide a quantitative assessment of disease status (dysplasia through carcinoma). This work retrospectively assesses seven biomarkers on a lesion-contralateral matched OCT dataset of lateral and ventral tongue (40 patients, 70 sites). Epithelial depth and loss of epithelial-stromal boundary visualization provide the strongest discrimination between disease states. The stroma optical attenuation coefficient provides distinction of benign lesions from dysplasia and carcinoma. The stratification biomarkers visualize subsurface changes which provides potential for future utility in biopsy site selection or treatment margin delineation.

Background: Radiotherapy in the head-and-neck area is one of the main curative treatment options. However, this comes at the cost of varying levels of normal tissue toxicity, affecting up to 80% of patients. Mucositis can cause pain, weight loss and treatment delay leading to worse outcomes and decreased quality of life. Therefore, there is an urgent need for an approach to predict normal mucosa response in patients prior to treatment. Methods: We here describe an assay to detect irradiation response in patient healthy oral mucosa tissue. Mucosa specimens from the oral cavity were obtained after surgical resection, cut into thin slices, irradiated, and cultured for three days. Seven samples were irradiated with X-ray and three additional samples were irradiated with both X-ray and protons. Results: Healthy oral mucosa tissue slices maintained normal morphology and viability for three days. We measured a dose-dependent response to X-ray irradiation and compared X-ray and proton irradiation in the same mucosa sample, using standardized automated image analysis. Furthermore, increased levels of inflammation inducing factors - major drivers in mucositis development - could be detected after irradiation. Conclusion: This model can be utilized for investigating mechanistic aspects of mucositis development and can be developed into an assay to predict radiation-induced toxicity in normal mucosa.

B-cell lymphoid malignancies is a heterogeneous group of hematologic cancers, where Bruton's tyrosine kinase (BTK) inhibitors have received FDA approval for several subtypes. The first-in-class covalent BTK inhibitor, ibrutinib, binds to the C481 amino acid residue to block the BTK enzyme and prevent the downstream signaling. Resistance to covalent BTK inhibitors can occur through mutations at the BTK binding site (C481S) but also other BTK sites and the phospholipase C gamma 2 (PLCγ2) resulting in downstream signaling. To bypass the C481S mutation, non-covalent BTK inhibitors, such as pirtobrutinib, were developed and are active against both wild-type and the C481S mutation. In this review, we discuss the molecular and genetic mechanisms which contribute to acquisition of resistance to covalent and non-covalent BTK inhibitors. In addition, we discuss the new emerging class of BTK degraders, which utilize the evolution of proteolysis-targeting chimeras (PROTACs) to degrade the BTK protein and constitute an important avenue of overcoming resistance. The moving landscape of resistance to BTK inhibitors and the development of new therapeutic strategies highlight the ongoing advances, that are being made towards the pursue of cure of B-cell lymphoid malignancies.

Elizabethkingia anophelis is an opportunistic pathogen causing lifethreatening infections in humans, particularly in immunocompromised patients, neonates and elderly. Infections caused by this species are exceptionally challenging to treat due to its multiresistance to antimicrobials. We report a case of central line-associated bloodstream infection by E. anophelis in a 2.5-year-old girl with acute lymphoblastic leukemia successfully treated with a combination of piperacillin/tazobactam and amikacin. The literature was also reviewed on paediatric infections caused by E. anophelis. Accurate identification with MALDI-TOF, or using molecular techniques, is crucial because of varying susceptibilities among species. Early, accurate diagnosis and prompt effective treatment optimize outcomes.

The nematode Caenorhabditis elegans, with its highly sensitive olfactory system, has emerged as a promising tool for testing chemotaxis. In the field of cancer diagnostics, there is a growing interest in the development of non-invasive screening methods for the detection of volatile organic compounds in a patient's urine. The objective of this study was to contribute to the existing body of knowledge by evaluating the ability of a Caenorhabditis elegans-based chemotaxis assay to discriminate between urine samples from healthy individuals and patients diagnosed with breast or colon cancer. Following synchronization of the developmental stages of C. elegans, nematodes were exposed to the urine of cancer patients and healthy individuals. Subsequently, chemotactic indices were calculated for each urine sample. Our results demonstrated a statistically significant difference in the chemotactic response of C. elegans to urine samples from cancer patients compared to healthy volunteers (p < 0.001). Moreover, the test exhibited promising diagnostic utility, with a sensitivity of 98%, a specificity of 62%, and a detection rate of 78%. Our findings expand on previous observations, confirming the remarkable sensitivity of C. elegans hermaphrodites to discriminating cancer-related volatile organic compounds in urine samples.

This review provides an overview of eXplainable AI (XAI) methods for oncological ultrasound image analysis and compares their performance evaluations. A systematic search of Medline Embase and Scopus between March 25 and April 14 2024 identified 17 studies describing 14 XAI methods, including visualization, semantics, example-based, and hybrid functions. These methods primarily provided specific, local, and post-hoc explanations. Performance evaluations focused on AI model performance, with limited assessment of explainability impact. Standardized evaluations incorporating clinical end-users are generally lacking. Enhanced XAI transparency may facilitate AI integration into clinical workflows. Future research should develop real-time methodologies and standardized quantitative evaluative metrics.

Abstract: Ovarian cancer (OC) ranks as the fifth most common cancer among women in the United States and globally, posing a significant health threat. Reactive oxygen species (ROS) have emerged as critical factors in the pathophysiology of this malignancy. ROS, characterized by their instability due to an unpaired electron, are involved in essential cellular functions and play a crucial role in the immune response under normal physiological conditions. However, an imbalance in ROS homeostasis, leading to excessive ROS production, results in oxidative stress (OS), which can cause indiscriminate damage to cellular structures and contribute to the pathogenesis of specific diseases, including OC. OC is primarily classified based on the originating cell type into epithelial, stromal, and germinal tumors, with epithelial tumors being the most prevalent. Despite advancements in medical technology, early detection of OC remains challenging, often leading to delayed treatment initiation. Current therapeutic approaches include surgical excision of tumor tissue, radiotherapy and chemotherapy. While these treatments are effective in early-stage OC, high mortality rates and frequent relapse underscore the urgent need for novel diagnostic and therapeutic strategies. This review aims to elucidate the role of ROS in OC, emphasizing the potential for developing innovative diagnostic tools and treatments that target ROS-mediated pathways. Given the critical impact of early detection and effective treatment, advancing our understanding of ROS in the context of OC could significantly enhance patient outcomes.

Neuroblastoma (NB) is a childhood cancer with heterogeneous characteristics, posing challenges to effective treatment. NBs express somatostatin receptors that facilitates the use of somatostatin analogs (SSTAs) as tumor-seeking agents for diagnosis and therapy. High-risk (HR) NBs often have gain-of-function mutations in the receptor tyrosine kinase anaplastic lymphoma kinase (ALK). Despite intensive multimodal treatment, survival rates remain below 40% for children with HR-NB. The aim of this work was to investigate the combined effect of the SSTA 177Lu-octreotide with the ALK inhibitor lorlatinib. Mice bearing human HR-NB CLB-BAR tumors were treated with lorlatinib, 177Lu-octreotide, combination of these pharmaceuticals or saline (control). Tumor volume was monitored and tumor samples were evaluated for cleaved caspase-3 and expression of 84 human genes involved in apoptosis. Combination treatment with 177Lu-octreotide and lorlatinib demonstrated synergistic antitumor effects. Increased number of cleaved caspase 3-positive cells was observed in tumors from mice treated with 177Lu-octreotide alone and in combination with lorlatinib. Modulation of Bcl-2 family gene expression was observed only in the presence of both 177Lu-octreotide and lorlatinib, with BID downregulated and HRK upregulated on days 2 and 7, respectively. The data suggests that ALK signaling pathway inhibition may contribute to radiosensitization in radionuclide therapy with 177Lu-octreotide.

Retinoblastoma (Rb) is a rare cancer that nonetheless represents the most common ocular malignancy in children. Rb exists as familiar and sporadic cancer and the increasing incidence of the sporadic one and its pathogenesis is mostly unknown. To date the management of retinoblastoma requires intensive chemotherapy and sometimes invasive surgery in order to preserve vision and quality of life in Rb patients. The discovery of the epigenetic nature of non-hereditable/sporadic Rb led to the development of high-throughput precision investigation strategies for the study of its epigenetic landscape. Here we investigated the effect of the demethylating 5-Aza-2’- deoxycytidine (Decitabine; DAC) agent on preclinical models to assess its possible use as anti-cancer drug in the treatment of Rb patients. We found that DAC treatment induced cell cycle arrest and apoptosis in Weri-Rb-1 cells. We investigated the variation of differential gene expression profile in Rb cells in relation to time of exposure to DAC with respect to controls. Network map analysis evidences 15 hub/driver genes, which share pathways of regulation of TNF-, FAS-, p53-dependent apoptotic signaling and NF-kB pro-survival pathways. Furthermore, a computing expression profile analysis of publicly available datasets of patients’ primary tumors and normal retina cell-derived organoids vs WeriWeri-Rb-1 DEGs depicted the relevancy of these 15 hub genes on retinoblastoma genesis. The antiproliferative effect of DAC treatment on Rb was confirmed in vivo, both in subcutaneous xenograft and orthotopic models also showing the changes the gene methylation status in treated Weri-Rb-1, shedding a new light on the reprogramming antiproliferative dynamics induced by the epigenetic therapy and on the role of this therapeutic approach to spare children sight and life.

Background: Potential calcium-related adverse events of vitamin D supplement use have not been addressed in large-scale, real-world data so far. Methods: Leveraging data from the UK Biobank, encompassing 445,493 individuals aged 40-69, we examined associations of high 25-hydroxyvitamin (25[OH]D) levels ≥100 nmol/L and vitamin D supplementation with hypercalcemia (plasma calcium >2.6 mmol/L), kidney stones, and atherosclerosis assessments (pulse wave arterial stiffness index and carotid intima-medial thickness). Regression models were comprehensively adjusted for 49 covariates. Results: Approximately 1.5% of the participants had high 25(OH)D levels, 4.3% regularly used vitamin D supplements, and 20.4% reported regular multivitamin use. At baseline, the hypercalcemia prevalence was 1.6%, and 1.1% were diagnosed with kidney stones during follow-up. High 25(OH)D levels were neither associated with calcium-related adverse events nor atherosclerosis assessments. Vitamin D and multivitamin supplementation were associated with an increased prevalence of hypercalcemia (odds ratios and 95% confidence intervals: 1.46[1.32-1.62] and 1.11[1.04-1.18], respectively) but were neither associated with atherosclerosis nor future kidney stones. Conclusion: High 25(OH)D levels observable in routine care were not associated with any adverse outcome. Vitamin D users have a slightly higher prevalence of hypercalcemia, possibly due to co-supplementation with calcium, but without higher atherosclerosis prevalence or risk of kidney stones.

Purpose: To simplify the application of optical coherence tomography (OCT) for examination of subsurface morphology in the oral cavity and reduce barriers towards adoption of OCT as a biopsy guidance device. The aim of this work was to develop automated software tools for simplified analysis of the large volume of data collected during OCT. Methods: Imaging and corresponding histopathology were acquired in-clinic using a wide-field endoscopic OCT system. An annotated dataset (n = 294 images) from 60 patients (34 male, 26 female) was assembled to train four unique neural networks. A deep learning pipeline was built using convolutional and modified u-net models to detect the imaging field of view (network 1), detect artifacts (network 2), identify the tissue surface (network 3), and identify the presence and location of the basement membrane (network 4). Results: The area under the curve of the image and artifact detection networks was 1.00 and 0.94 respectively. The Dice similarity score for the surface and basement membrane segmentation networks was 0.98 and 0.83 respectively. Conclusion: Deep Learning (DL) techniques can identify the location and variations in the epithelial surface and basement membrane in OCT images of the oral mucosa. Segmentation results can be synthesized into accessible en face maps to allow easier visualization of changes.

This review explores the nuanced decision-making surrounding postoperative radiotherapy for diffuse low-grade glioma (DLGG) patients, emphasizing the need for personalized treatment to balance the benefits of tumor control with the risks of long-term side effects. Radiotherapy is a cornerstone of DLGG treatment, offering significant improvements in progression-free survival, but its potential for cognitive decline and vascular lesions necessitates careful consideration of individual patient factors. The review delves into the complexities of radiotherapy timing, revealing that while early radiotherapy enhances progression-free survival, it does not significantly impact overall survival and may lead to earlier onset of cognitive decline. Conversely, delayed radiotherapy may mitigate cognitive decline but may result in shorter progression-free survival and the onset of neurological symptoms. The review advocates for a patient-centered approach, emphasizing the importance of weighing individual risks and benefits, and highlights the potential of artificial intelligence in predicting cognitive decline and the need to revisit previous research findings in light of the 2021 WHO (World Health Organization) classification update, underscoring the evolving nature of DLGG treatment and the ongoing quest for optimal therapeutic strategies.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors, including abemaciclib, have been approved for the treatment of hormone receptor-positive, HER2-negative advanced, and metastatic breast cancer. Despite the high therapeutic efficacy of CDK4/6 inhibitors, they are associated with various adverse effects, including potentially fatal interstitial lung disease. Therefore, a combination of CDK4/6 inhibitors with letrozole or fulvestrant has been attempted but has demonstrated limitations in reducing adverse effects, highlighting the need to develop new combination therapies. This study proposes a combination strategy using CDK4/6 inhibitors and tricyclic antidepressants to enhance the therapeutic outcomes of these inhibitors while reducing their side effects. The therapeutic efficacies of abemaciclib and desipramine were tested in different cancer cell lines (H460, MCF7, and HCT-116). The antitumor effects of the combined abemaciclib and desipramine treatment were evaluated in a xenograft colon tumor model. In vitro cell studies have showed the synergistic anticancer effects of combination therapy in the HCT-116 cell line. The combination treatment significantly reduced tumor size compared with control or single treatment without causing apparent toxicity to normal tissues. The combination of abemaciclib and desipramine may be a promising therapeutic strategy as they could reduce side effects and enhance tumor suppression.

In the field of 2-D image processing and computer vision, accurately detecting and segmenting objects in scenarios where they overlap or are obscured remains a challenge. This difficulty is worse in the analysis of shoeprints used in forensic investigations because they are embedded in noisy environments such as the ground and can be indistinct. Traditional Convolutional Neural Networks (CNNs), despite their success in various image analysis tasks, struggle with accurately delineating overlapping objects due to the complexity of segmenting intertwined textures and boundaries against a background of noise. This study introduces employs the YOLO (You Only Look Once) model enhanced by edge detection and image segmentation techniques to improve the detection of overlapping shoeprints. By focusing on the critical boundary information between shoeprint textures and the ground, our method demonstrates improvements in sensitivity and precision, achieving confidence levels above 85% for minimally overlapped images and maintaining above 70% for extensively overlapped instances. Heatmaps of convolution layers were generated to show how the network converges towards successful detection using these enhancements. This research may provide a potential methodology for addressing the broader challenge of detecting multiple overlapping objects against noisy backgrounds.

Early detection of pancreatic ductal adenocarcinoma (PDAC) requires further examination after selecting cases with risk factors for the condition, such as family history, hereditary pancreatic carcinoma syndrome, intraductal papillary mucinous neoplasms, or chronic pancreatitis. The Japan Study Group on the Early Detection of Pancreatic Cancer has investigated and clarified the clinicopathological features for the early diagnosis of PDAC. Further approaches for the early diagnosis of PDAC are warranted.

This review explores the challenges and emerging trends in pancreatic cancer therapy. In particular, we focus on the tumor microenvironment and the potential of immunotherapy in pancreatic cancer. We discuss novel strategies targeting the desmoplastic barrier and immunosuppressive cells to enhance immune cell infiltration and activation. Recent clinical trials, particularly those involving novel immunotherapeutic agents and tumor vaccines, are examined to understand their efficacy and limitations. This review aims to highlight the ongoing efforts to refine immunotherapy approaches for better patient outcomes.

Background: Health care providers (HCPs) may required to initiate a cardiopulmonary resuscitation (CPR) while patients are in a prone position. Healthcare providers must possess the necessary information, abilities and experience to do cardiopulmonary resuscitation in a prone position (PPCPR) confidently. Aim: This study aimed to assess healthcare providers' (HCPs) preparedness to perform cardiopulmonary resuscitation in a prone position at specialized units in Jordan's healthcare sectors. Methods: In eight tertiary hospitals, a descriptive cross-sectional survey was carried out. An on-line questionnaire was conducted among 332 healthcare professionals who are employed in operating rooms, intensive care units or interventional procedure rooms. Results: Preparedness levels among healthcare providers were 24.4% excellent, 2.1% acceptable and 73.5% poor. The average preparedness score was 32.38 (SD = 39.90), indicating significant variability. A lack of targeted training was associated with lower preparedness levels. Notably, providers with Advanced Cardiac Life Support (ACLS) training showed significantly higher preparedness. Conclusion: The HCPs in Jordan are poorly prepared to perform PPCPR whenever indicated. However, the study findings represent a significant step towards improving HCPs' preparedness to perform PPCPR. They serve as a baseline assessment and highlight the gaps in HCPs' readiness, which help their organizations develop and implement targeted training strategies and interventions. Nevertheless, incorporating this training in the hospital orientation, training policies, and clinical guidelines is equally important to enhance their capabilities for better outcomes. Implications for Clinical Practice: The findings emphasize the urgent need for hospitals to integrate PPCPR training into their standard orientation and ongoing training programs. Providing comprehensive ACLS training and regular PPCPR drills will enhance HCPs' competence and confidence, leading to improved patient outcomes during emergency situations involving prone position CPR.

Issues presented by the application of monoclonal antibodies in diagnostic assays and as curative agents can make the use of such molecules cost-prohibitive and sometimes even unsafe. This has warranted the development of short single-stranded oligonucleotides known as Aptamers. The structural malleability of these short DNA or RNA nucleotide segments allows them to exist in distinct conformations. SELEX (Systematic Evolution of Ligands by Exponential Enrichment) is a multi-step process for synthesis of aptamers. Each step of this procedure is governed by a diverse set of factors that influence production efficiency, binding affinity, and specificity of the oligonucleotides. Headway in aptamer research has been made in recent years by the introduction of newer iterations of the SELEX process. A greater number of studies are now being carried out to incorporate aptamers into existing disease detection tools and therapies. An overview has been given first on the key aptamer properties and the process of their production (with its newer iterations), contrasting each of them with that of monoclonal antibodies. Possible manifold applications afforded due to unique aptamer characteristics are also discussed. A keen review is further provided on the design, development and use of fluorescent aptamers in bioimaging, sequencing or profiling, and treatment of pathogenic bacteria and tumor cells.

Multi-cancer early detection (MCED) tests are being developed, but little is known about patient receptivity to their use for cancer screening. The current study assessed patient interest in such testing. Our team conducted a prospective, observational study among primary care patients in a large, urban health system. They were asked to complete a telephone survey that briefly described a new blood test in development to identify multiple types of cancer, but was not currently recommended or covered by insurance. The survey included items to assess respondent background characteristics, perceptions about MCED testing, and interest in having such an MCED test. We also used multivariable analyses to identify factors associated with patient interest in test use. In 2023, we surveyed 159 (32%) of 500 identified patients. Among respondents, 125 (79%) reported a high level of interest in having an MCED test. Interest was not associated with personal background characteristics, but was positively associated with the following expectations: testing would be recommended for cancer screening, be convenient, and be effective in finding early-stage disease (OR=11.70, 95% CI: 4.02, 34.04, p < 0.001). Research is needed to assess patient interest and actual uptake when detailed information on testing is presented in routine care.

Kisspeptin, a key neuropeptide derived from the KISS1 gene, is renowned for its critical role in regulating the hypothalamic-pituitary-gonadal axis and reproductive hormone secretion. Beyond its primary function in reproductive biology, emerging research has illuminated its influence in various cancers, mediating significant effects through its interaction with the G-protein coupled receptor, Kisspeptin receptor. This interaction has been implicated in modulating cellular pro-cesses such as proliferation and metastasis, making it a potential target for therapeutic interven-tion. Our study initially screened ten kisspeptin-10 analogs through cytotoxic effects of kisspep-tin-10 (KP10) and its analogs in several cancer types, including cervical, prostate, breast, and gastric cancers, with a particular focus on cervical cancer where the most profound effects were observed. Further exploration using kinase array assays revealed that these analogs specifically alter key kinases involved in cancer progression. Migration assays demonstrated a substantial decrease in cell motility, and Bioluminiscence Resonance Energy Transfer assays confirmed these analogs strong interactions with the kisspeptin receptor. Overall, our results indicate that these KP10 analogs not only hinder cervical cancer cell proliferation but also curtail migration through targeted modulation of kinase signaling, suggesting their potential as therapeutic ayfgents in managing cervical cancer progression. This comprehensive approach underscores the therapeutic promise of exploiting kisspeptin signaling in cancer treatment strategies.

Age-related diseases place an intense and growing stress on healthcare systems. Numerous theories of ageing exist. Yet prediction, prevention and treatment limitations of age-related disease persist because we lack a complete aetiological understanding of their origins. Here we propose a new theory that aims to provide a blueprint-type understanding of ageing and disease aetiology, working across multiple scientific disciplines. Supported by specific examples, we demonstrate that the primary driver of much of age-related diseases is the futile triggering of specific molecular pathways in a pathological manner, which we term patho-pathways. Patho-pathways induce pathological cell, tissue and system changes in the form of hyperactivity (undesirable increased and new biological activities that are typical of age related disease). As part of patho-pathways, all wild-type (normal) genes have the potential to contribute to age-related diseases (though specific risk varies and can be formularised). In a domino-style effect, one patho-pathway typically triggers others, resulting in complex, but traceable, cascades. Utility, in terms of changing clinical and scientific practice, is derived from mapping these cascades to create Blueprint Maps that allow identification of biomarkers and therapeutic targets far upstream in the causal chain of events. Finally, our theory provides testable hypotheses concerning predictions of links between otherwise seemingly disparate diseases as well as new interventions into ageing.

Multiple Myeloma (MM), is a hematological malignancy and poses significant therapeutic challenges. This review synthesizes evidence from pivotal clinical trials to guide induction treatment for transplant-eligible (TE), newly diagnosed MM (NDMM) patients. Emphasizing the evolution from three-drug to four-drug induction therapies, we highlight the integration of monoclonal antibodies, particularly CD38 recombinant monoclonal antibody agents, into treatment regimens. Our analysis includes a comprehensive literature review of research from major databases and conferences conducted between 2010 and 2024, culminating in the detailed evaluation of 47 studies. The findings underscore the superiority of quadruple regimens in TE NDMM, notably those incorporating daratumumab, in achieving superior responses including progression-free survival (PFS), minimal residual disease (MRD) negativity, overall response rate (ORR), and overall survival (OS) when compared to triple-drug regimens. As treatment regimens evolve with additional agents, the improved outcomes with treatment-related adverse events should be carefully balanced. This review advocates for a paradigm shift towards quadruple induction therapies for TE NDMM, offers a detailed insight into the current landscape of MM treatment, and reinforces a new standard of care.

Introduction: Gastric cancer (GC) is one of the most common cancers in the world. It is a very aggressive and heterogeneous tumor. GC does not cause symptoms, so it is often diagnosed in an advanced stage and associated with poor prognosis. Despite new treatment options, it still remains a therapeutic problem. An important element determining the method of treatment of locally advanced gastric cancer (LAGC) is the assessment of lymph node metastases in preoperative and postoperative imaging and/or histopathological examination.Aim: The assessment of lymphovascular invasion (LVI) in histopathological examination in patients with LAGC after gastrectomy. The groups of patients were divided into patients who received preoperative chemotherapy, patients without preoperative chemotherapy, and all patients. Additionally, we assessed the correlation between the presence of LVI and the number of lymph nodes collected during gastrectomy.Material and method: We collected patients with histologically confirmed GC after gastrectomy. The collected samples were divided into three subgroups: patients with neoadjuvant chemotherapy (NAC), patients without NAC, and all patients. Histopathological examination assessed the presence of LVI infiltration. We then assessed the correlation between the presence of LVI and the presence of lymph node metastasis in GC. Additionally, we assessed the correlation between LVI and the number of lymph nodes evaluated in patients in each group. The statistical analyses were performed using Statistica v13.3 and Microsoft Excel 2021. The significance limit was set at p<0.05.Results:The presence of LVI strongly correlated with node involvement, and the result was statistically significant in all patients and the group of patients treated with NAC. The difference was not statistically significant in the group not treated by NAC. Additionally, we did not observe a correlation between the presence of LVI and the number of metastatic lymph nodes in GC.Summary and Conclusions: The presence of LVI in a patient with GC indicates a high probability of lymph node metastasis, which should translate into therapeutic procedures. Assessment of LVI may help identify potential patients with lymph node metastases, particularly in patients undergoing endoscopic resection without planned lymphadenectomy. It is advisable to expand research on a larger scale in order to establish clear standards in this area.

The IMbrave150 trial established atezolizumab with bevacizumab (A+B) as standard care for hepatocellular carcinoma (HCC), recommending an esophagogastroduodenoscopy (EGD) within 6 months of treatment initiation to prevent bleeding from esophagogastric varices. The necessity of mandatory EGD for all patients remains unclear. We retrospectively analyzed 112 HCC patients treated with A+B at five Canadian cancer centers from July 1, 2020, to August 31, 2022. A+B was the first-line therapy for 90% of patients, with median overall survival at 20.3 months and progression-free survival at 9.6 months. There was no survival difference between patients with bleeding and those without. Before A+B, 71%(79) of patients underwent an EGD within 6 months, revealing varices in 41%(32) and requiring intervention in 19%(15). The overall bleeding rate was 15%(17), with GI-specific bleeding occurring in 83%(5) of the EGD group and 17%(1) of the non-EGD group (p=0.24). Non-GI bleeding was observed in 10%(11) of patients. Outcomes for HCC patients treated with A+B in Canada were comparable to IMbrave150. Our study showed twice the rate of varices detection and treatment compared to IMbrave150, reflecting real-world treatment of high-risk populations. There was no increased GI bleeding in patients without pre-treatment EGD, supporting a selective EGD approach.

Thyroidectomy has been post-operatively managed by hormone replacement therapy in order to satisfy the reference ranges of thyroid stimulating hormone (TSH) and thyroxine (T4) levels. While medication and standardized reference ranges have proven to be effective, many patients continue to report unintentional weight gain despite adequate amounts of treatment and levels of TSH and T4. Physicians, over the years, have become complacent to these “normal” ranges, and have ignored the metabolic consequences that are affecting thyroidectomy patients. This paper aims to redefine the approach to post-thyroidectomy clinical care by: challenging the current standardized hormonal range values, exploring the gaps in thyroid hormone conversion, investigating the metabolic pathways of T3, considering the influence of inflammatory markers, and proposing the future for patient-centered management.

The combination of immunoPET—where an antibody (Ab) is labeled with an isotope for PET imaging—and radioimmunotherapy (RIT), using the same antibody with a therapeutic isotope, offers significant advantages in cancer management. ImmunoPET allows non-invasive imaging of antigen expression, which aids in patient selection for a subsequent radioimmunotherapy. It also facilitates the assessment of tumor response to therapy, allowing for treatment adjustments if necessary. In addition, immunoPET provides critical pharmacokinetic data, including antibody biodistribution and clearance rates, which are essential for dosimetry calculations and treatment protocol optimization. There are still challenges to overcome. Identifying appropriate target antigens that are selectively expressed on cancer cells while minimally expressed on normal tissues remains a major hurdle to reduce off-target toxicity. In addition, it is critical to optimize the pharmacokinetics of radio-labeled antibodies to maximize tumor uptake and minimize normal tissue uptake, particularly in vital organs such as the liver and kidney. This approach offers the potential for targeted and personalized cancer therapy with reduced systemic toxicity by exploiting the specificity of monoclonal antibodies and the cytotoxic effects of radiation. However, further research is needed to address remaining challenges and to optimize these technologies for clinical use.

In recent years, computer-aided analysis techniques have emerged as valuable tools in assisting dermatologists by providing objective and efficient analysis of skin cancer images. This paper utilizes the combination of the Contourlet Transform (CT) and Local Binary Pattern (LBP) techniques for accurately recognizing borders, contrast changes, and shapes of skin cancer images. These results often contain many features, leading to high computational costs and potential over-fitting issues. Hence, we applied Particle Swarm Optimization (PSO) to select the most informative and discriminating features, reducing the dimensionality while retaining important information for accurate classification. After reducing the feature set with PSO, we applied these sets to Machine learning classification algorithms: Support Vector Machine (SVM), Random Forest (RF), and Neural Networks (NN). The results show that SVM has the lowest time complexity of 0.0458 seconds, followed by the Neural Network at 0.08730 seconds, and the Random Forest model has the highest time complexity of 0.1622 seconds. The SVM and Neural Network models are faster to train than the Random Forest model, making them more suitable for real-time or latency-sensitive applications. We also compared our proposed model with the state-of-the-art models and obtained the accuracy of 86.9%, which is the highest among the models.

Lung cancer is the leading cause of cancer mortality worldwide, and it is urgently necessary to diagnose it as early as possible. Usually, the diagnostic process begins with a radiological examination which, when a possible tumour is present, is followed by a biopsy to extract tissue samples from the patient's lungs. Therefore, the purpose of this study is the development of an artificial intelligence algorithm that will analyse the Whole Slide Image (WSI) generated by the digitisation of the glass slides obtained from the extracted samples and detect if there is a tumour. The developed learning algorithms as well as the tested neural networks (NNs) were trained on a dataset composed of previously annotated WSI tiles, classified as Tumour or Non-Tumour. From these, four developed convolutional neural networks stood out and were selected to be compared with each other and with the tested NNs. When the best result of each of the developed architectures was compared to the highest result of the tested NNs, it was possible to denote that version 4 of CancerDetecNN achieved an average accuracy of 89.749 \% and an average loss of 0.220. Furthermore, the results for the four selected versions are in agreement with the results reported in the literature, however, the limited size of the given dataset must be considered. Given the results obtained, the fourth version has the potential to optimise the lung cancer diagnosis process.

Lung cancer (LC) continues to be an important public health problem being the most common form of cancer and a major cause of cancer deaths worldwide. Despite the great bulk of research to identify genetic susceptibility genes by genome-wide association studies, only few loci associated to nicotine dependence have been consistently replicated. Our previously published study in few phenotypically discordant sib-pairs identified a combination of germline truncating mutations in known cancer susceptibility genes in never smoker early-onset LC patient does not present in their healthy sib. These results firstly demonstrated the presence of an oligogenic combination of disrupted cancer predisposing genes in non-smokers patients, giving experimental support to a model of a “private genetic epidemiology”. Here, we used a combination of whole-exome and RNA sequencing coupled with a discordant sib’s model in a novel cohort of pairs of never-smokers early-onset LC patients and in their healthy sibs used as controls. We selected rare germline variants predicted as deleterious by CADD and SVM bio-informatics tools and absent in the healthy sib. Overall, we identified an average of 200 variants per patient, about 10 of which in cancer predisposing genes. In most of them, RNA sequencing data reinforced the pathogenic role of the identified variants showing: i) downregulation in LC tissue (indicating “second hit” in tumor suppressor genes); ii) upregulation in cancer tissue (likely oncogene); iii) downregulation in both normal and cancer tissue (indicating transcript instability). The combination of the two techniques demonstrates that each patient has an average of six (with a range from four to eight) private mutations with functional effect in tumor predisposing genes. The presence of a unique combination of disrupting events in the affected subjects may explain the absence of familial clustering of non-small cell lung cancer. In conclusion, these findings indicate that each patient has his/her own “predisposing signature” to cancer development and suggest the use of personalized therapeutic strategies in lung cancer.

Exosomal microRNAs (miRNAs) from cancer cells play a key role in mediating the oral squamous cell carcinoma (OSCC) microenvironment. The objective aimed to investigate how long non-coding RNA (lncRNA) MEG3 affects OSCC angiogenesis through exosomal miR-421. Global miRNA microarray analysis and quantitative real-time PCR (qRT-PCR) were performed to determine the level of miRNAs in OSCC cells-derived exosomes. Cell migration, invasion, tube formation, immunohistochemistry and hemoglobin concentration were used to study the effects of exosomal miR-421 in angiogenesis. Western blotting was used to determine the expression level of HS2ST1 and VEGFR2-related downstream proteins. MiRNA array and qRT-PCR identified upregulation of miR-421 in OSCC cell-derived exosomes. Furthermore, exosome-miR-421 can be taken up by human umbilical vein endothelial cells (HUVEC) and then targets HS2ST1 through VEGF-mediated ERK and AKT phosphorylation, thereby promoting HUVEC migration, invasion, and tube formation. Additionally, enforced expression of lncRNA MEG3 in OSCC cells reduced exosomal miR-421 levels and then increased HS2ST1 expression, thereby reducing the VEGF/VEGFR2 pathway in HUVEC. Our results demonstrate a novel mechanism by which lncRNA MEG3 can act as a tumor suppressor and regulate endothelial angiogenesis through the exosomal miR-421/HS2ST1 axis, which provides a potential therapeutic strategy for OSCC angiogenesis.

Biologists seek to identify a small number of significant features that are important, non-redundant, and relevant from diverse omics data. For example, statistical methods like LIMMA and DEseq distinguish differentially expressed genes between a case and control group from the transcript profile. Researchers also apply various column subset selection algorithms on genomics datasets for a similar purpose. Unfortunately, genes selected by such statistical or machine learning methods are often highly co-regulated, making their performance inconsistent. Here, we introduce a novel feature selection algorithm that selects highly disease-related and non-redundant features from a diverse set of omics datasets. We successfully applied this algorithm to three different biological problems: a) disease to normal sample classification, b) multiclass classification of different disease samples, and c) disease subtypes detection. Considering classification ROC-AUC, False-positive, and False-negative rates, our algorithm outperformed other gene selection and differential expression (DE) methods for all six types of cancer datasets from TCGA considered here for binary and multiclass classification problems. Moreover, genes picked by our algorithm improved the disease subtyping accuracy for four different cancer types over the state-of-the-art methods. Hence, we posit that our proposed feature reduction method can support the community to solve various problems, including the selection of disease-specific biomarkers, precision medicine design, and disease sub-type detection.

Lung cancer, including both non-small cell lung cancer and small cell lung cancer, remains the leading cause of cancer-related mortality worldwide representing 18% of the total cancer deaths in 2020. Many patients are identified already at an advanced stage with metastatic disease and have a worsening prognosis. Recent advances in the genetic understanding of lung cancer have opened new avenues for personalized treatments and targeted therapies. This review examines the latest discoveries in the genetics of lung cancer, discusses key biomarkers, and analyzes current clinical therapies based on this genetic information. It will conclude with a discussion of future prospects and potential research directions.

Lung cancer is the leading cause of cancer death worldwide therefore studies about the etiological factors and carcinogenesis are important.The aim of the study is to detect the presence and types of Human papilloma virus (HPV) in lung cancer and non-tumoral lung and Epidermal Growth Factor Receptor (EGFR) mutation prevalance in lung cancer with Polymerase Chain Reaction (PCR) method.Fifty patients who were histopathologically diagnosed lung cancer and 7 patients with non-neoplastic lung disease were enrolled in the study. HPV positivity was detected in 75.4% of the patients. The rate of high-risk HPV positivity was 100% in adenocarcinomas, 64.5% in squamous cell carcinomas, and 57% in non-neoplastic lung. HPV 51 was the most frequent type followed by HPV 16 (43.9%). There was no statistically significant relationship between HPV infection and age, gender and smoking history and EGFR mutation. The prevalence of HPV positivity is variable in lung cancer in different studies and this may be due to many factors including HPV detection methods, number of patients, geographic regions. New studies about the role of HPV infection need to be performed in order to obtain information about the use of prophylactic and theurepatic agents in lung cancer.

Melanoma is the most aggressive form of skin cancer. In the advanced stage of development it is resistant to currently available therapeutic modalities. Increased invasiveness and metastatic potential depend on a number of proteins involved in various signal transduction pathways. Hippo signaling plays an important role in malignant transformation. Dysfunctions of the Hippo pathway initiate the expression of tumor growth factors and is associated with tumor growth and metastasis formation. This review summarizes the recent achievements in studying the role of the Hippo pathway in melanoma pathogenesis and points to the potential specific targets for anti-melanoma therapy.

Human papillomavirus (HPV) uses the cellular trafficking machinery to reach the cell nucleus and initiate a successful infection. The HPV capsid consists of two proteins: L1 (the major capsid protein) and L2 (minor capsid protein), and L2 is known to be responsible for trafficking the viral genome to the nucleus. From previous studies, we know that many cellular proteins interact with L2 and are involved in the trafficking process at different stages of the infectious entry process. To further investigate how HPV-16 achieves successful viral entry, we have performed a mass spectrometry analysis to identify novel interacting proteins that associate with incoming HPV-16 virions. We show that HPV-16 pseudovirions interact with a group of cellular cargo proteins (COPI), and here we confirm that this is mediated by the direct binding of L2, but not L1, to the COPB1 subunit. We also show that the ability of L2 to interact with COPB1 is conserved in both low- and high-risk HPV types. Furthermore, we also show that the interaction is essential for successful infection entry of multiple HPV types, thereby identifying a novel constituent of the infectious entry pathway of the HPV.

Many risk-modifying factors affect cancer incidence and mortality rates. We present an ecological study of incidence and/or mortality rates for cancers during 2007–2016 of 17 anatomical sites with respect to solar ultraviolet-B (UVB) doses and obesity prevalence. Solar UVB reduces cancer risk by producing vitamin D, which has many mechanisms to reduce risk of cancer incidence, progression, and metastasis. Obesity increases cancer risk through several mechanisms, including increased systemic inflammation. Data were averaged for 12 geographical regions. Solar UVB doses were significantly inversely correlated with mortality rates for five cancers for males and four for females. Obesity prevalence was directly correlated with mortality rates for three cancers for males and seven for females. The population attributable fraction of cancer mortality rates ascribed to low solar UVB dose was 0.03 for both males and females, whereas that for obesity prevalence was 0.05 for males and 0.08 for females. Thus, cancer mortality rates in France could be reduced through vitamin D supplementation and reducing the prevalence of obesity. Doing so also could reduce risk of other adverse health outcomes.

The number of long-term cancer survivors increases continually. Understanding their needs is crucial to ensure an adequate follow-up. The aim of our study was to summarize the current literature concerning needs and what in-fluences these needs. A Scoping review of systematic reviews was conducted according to the recommendations of the Joanna Briggs Institute (JBI). Four electronic databases were searched. Of 414 retrieved papers, 11 met the eligi-bility criteria. Needs were aggregated into six domains (health-related information, health system, mental, practical, relationship and physical) and 15 categories. The lack of adequate information and the lack of access and/or conti-nuity of supportive care were the most prominent needs. Female gender, younger age, a low level of family and/or social support, and higher educational level were identified as risk factors. Employment and relationship status can affect the needs both in a positive or negative way. The weeks or months after the end of the treatments are partic-ularly critical and needs can be emphasized during this period. Cancer survivors could also leave positive changes. The variety of needs affects the quality of life of cancer survivors. The current Swiss healthcare system is not de-signed to support these people. Needs assessments should be systematically provided to ensure a better awareness on the part of health professionals and to allow an individual, holistic, and integrated follow-up.

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with complex carcinogenesis. Although there has been significant progress in the treatment of HCC over the past decades, drug resistance to chemotherapy remains a major obstacle in its successful management. In this study we were able to reduce chemoresistance in cisplatin-resistant HepG2 cells by either silencing the expression of transglutaminase type 2 (TG2) using siRNA or by pre-treatment of cells with the TG2 enzyme inhibitor cystamine. Further analysis revealed that, whereas the full-length TG2 isoform (TG2-L) was almost completely cytoplasmic in its distribution, the majority of the short TG2 isoform (TG2-S) was membrane-associated in both parental and chemoresistant HepG2 cells. Following induction of cisplatin toxicity in non-chemoresistant parental cells, TG2-S together with cisplatin quickly relocated to the cytosolic fraction. Conversely, no cytosolic relocalisation of TG2-S or nuclear accumulation cisplatin was observed following identical treatment of chemoresistant cells, where TG2-S remained predominantly membrane-associated. This suggests that deficient subcellular relocalisation of TG2-S from membranous structures into the cytoplasm may limit the apoptic response to cisplatin toxicity in chemoresistant cells. Structural analysis of TG2 revealed the presence of binding motifs for interaction of TG-S with the membrane scaffold protein LC3/LC3 homologue that could contribute to a novel mechanism of chemotherapeutic resistance in HepG2 cells.

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning based on deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and we discuss the learning mechanism of MetGen. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironment, such as immune response and the metastasis process, which potentially fosters a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

Lynch syndrome (LS) is an inherited disorder in which affected individuals have a significantly higher-than-average risk of developing colorectal and non-colorectal cancers, often before the age of 50 years. In LS, mutations in DNA repair genes lead to a dysfunctional post-replication repair system. As a result, the unrepaired errors in coding regions of the genome produce novel proteins, called neoantigens. Neoantigens are recognised by the immune system as foreign and trigger an immune response. Due to the invasive nature of cancer screening tests, universal cancer screening guidelines unique for LS (including colonoscopy) are poorly adhered to by LS variant heterozygotes (LSVH). Currently, it is unclear whether immunogenomic components produced as a result of neoantigen formation can be used as novel biomarkers in LS. We hypothesize that: (i) LSVH produce measurable and dynamic immunogenomic components in blood, and (ii) these quantifiable immunogenomic components correlate with cancer onset and stage. Here, we discuss feasibility and propose the potential to: (a) identify personalised novel immunogenomic biomarkers, (b) reduce invasive cancer screening tests and thus increase non-invasive cancer surveillance, (c) improve compliance and adherence to recommended cancer screening guidelines in LSVH.

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin and lesions, automatic identification of skin cancer is complicated. The rate of human death can be massively reduced if melanoma skin cancer can be detected quickly using dermoscopy images. In this research, an anisotropic diffusion filtering method is used on dermoscopy images to remove multiplicative speckle noise and the fast-bounding box (FBB) method is applied to segment the skin cancer region. Furthermore, the paper consists of two feature extractor parts. One of the two features extractor parts is the hybrid feature extractor (HFE) part and another is the convolutional neural network VGG19 based CNN feature extractor part. The HFE portion combines three feature extraction approaches into a single fused feature vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF). The CNN method also is used to extract additional features from test and training datasets. This two-feature vector is fused to design the classification model. This classifier performs the classification of dermoscopy images whether it is melanoma or non-melanoma skin cancer. The proposed methodology is performed on two ordinary datasets and achieved the accuracy 99.85%, sensitivity 91.65%, and specificity 95.70%, which makes it more successful than previous machine learning algorithms.

Introduction: Signet-ring cells are typically associated with mucin-secreting epithelium thus most commonly found in a gastrointestinal tract, however not exclusively. Primary signet ring cell carcinoma of the prostate is a rare and poorly differentiated, aggressive acinar adenocarcinoma variant with a grim prognosis. Clinical case: In June of 2023 a 54-year-old Caucasian male came to the hospital complaining of lower urinary tract obstructive symptoms with occasional macrohematuria, non-specific body aches, and shortness of breath. A prostate specimen obtained in transurethral resection of the prostate was sent for histopathological examination. After a series of extraprostatic diagnostic workups including fibrogastroduodenoscopy, colonoscopy computed tomography imaging, and immunohistochemical studies, the patient was diagnosed with primary prostatic signet-ring cell adenocarcinoma st. IV. Unfortunately, the patient with the disease this advanced, PE, and third-degree thrombocytopenia was not a candidate for chemotherapy and died of cardiopulmonary insufficiency later that week. Discussion: Prostatic signet-ring cell carcinoma accounts for 0.02% of all prostate adenocarcinoma cases. Due to its nature and epidemiology, a diligent extraprostatic investigation has to be carried out. The disease often presents with unremarkable clinical symptoms and variable serum prostate-specific antigen results which may contribute to its late diagnosis which together with inconsistent immunohistochemical findings and unpredictable response to hormonal treatment pose both diagnostic and therapeutic challenges that negatively affect the prognosis. Conclusion: The study highlights the importance of a multidisciplinary approach and the need for diagnostic and therapeutic consensus within the research community in search of the primary site of the disease which may positively influence the prognosis.

The growing expansion of the economy and population has resulted in an increased inclination towards the utilization of groundwater resources. Conducting a geophysical survey is a widely employed method for subsurface mapping and the detection of groundwater. A geophysical study was conducted in Nanshan township, Huarong County, located in the Hunan province of the South-Central region of China. The investigation involved the utilization of a 2D Electrical Resistivity Imaging technique employing forward and inverse pole-dipole electrode array. A total of six survey lines were established, each with an electrode distance from the nearest measuring point to exceeding 800 m. The maximum current electrode separation was utilized in this setup. The spacing between the electrical resistivity sounding points was established at regular intervals. The findings from the exploration indicate the existence of multiple faults within the surveyed region. The study additionally identified two regions of structural failure, which occurred due to the convergence of faults oriented in different directions. This convergence led to the fracturing of rocks, an increase in water content, and a decrease in resistivity. The findings from the exploration were utilized in the formulation of five verification target boreholes. The results of this study offer significant insights that can inform future investigations into groundwater exploration endeavors within the region.

The Infierno glacier is located in Aragon (Spain), Pyrenees mountain range, southern slope, the only one in this country that still preserves white glaciers. These are the southernmost glaciers in Europe and are currently in rapid regression. The work analyzes the evolution of the glacier between 2016 and 2022 (taking as "year zero" or starting point, 2015). In addition to the observations on the glacier itself, the variables (precipitation, temperatures, snow volumes and thicknesses) that allow understanding this evolution are studied. The results offer strong regression, with thickness losses in that period of 4.6 m and retreat of its front of 14.9 m. The evolution has frequent trend changes, linked to the interannual climatic irregularity characteristic of this mountain range. The main explanatory factor is the thermal increase. The thermal anomalies with respect to the average reference values have increased, in this period, +0.55° C. The year 2022 has been particularly warm and has recorded the greatest regression of the glacier (between May and August, the thermal anomalies were between +4° C and +2° C). Regarding precipitations, they have irregular tendencies and show a decreasing trend (-9% in the same period of time).

The popularity of handheld devices for point-of-care ultrasound (POCUS) has increased in recent years due to their portability and cost-effectiveness. However, POCUS has the drawback of lower imaging quality compared to conventional ultrasound, because of hardware limitations. Improving the quality of POCUS through post-image processing would therefore be beneficial, with deep learning approaches showing promise in this regard. This review investigates the state-of-the-art progress of image enhancement using deep learning suitable for POCUS applications. A systematic search was conducted from January 2024 to February 2024 on PubMed and Scopus. From the 457 articles that were found, the full text was retrieved for 69 articles. From this selection, 15 articles were identified addressing multiple quality enhancement aspects. A disparity in the baseline performance of the low-quality input images was seen across these studies, ranging between 8.65–29.24 dB for the Peak Signal-to-Noise Ratio (PSNR) and 0.03-0.71 for the Structural Similarity Index Measure (SSIM). In six studies, where both PSNR and the SSIM metrics were reported for the baseline and the generated images a mean difference of 6.60 (SD ± 2.99) and 0.28 (SD ± 0.15) was observed for the PSNR and SSIM, respectively. The reported performances demonstrate the potential of deep-learning-based image enhancement for POCUS. However, variability in the extent of performance gain across datasets and articles was notable, and the heterogeneity across articles makes quantifying the exact improvements challenging.

With advancements in digital technologies such as 5G communications, big data, and cloud computing, the components of network operation systems have become increasingly complex, significantly complicating system monitoring and maintenance. Correspondingly, automated log anomaly detection has become a crucial means to ensure stable network operation and protect them from malicious attacks or failures. Conventional machine learning and deep learning methods assume consistent distributions between the training and testing data, adhering to a closed-set recognition paradigm. Nevertheless, in realistic scenarios, systems may encounter new anomalies that were not present in the training data, especially in log anomaly detection. Inspired by evidential learning, we propose a novel anomaly detector called LogEDL, which supervises training of the model through an evidential loss function. Unlike traditional loss functions, the evidential loss function not only focuses on correct classification, but also quantifies the uncertainty of predictions. This enhances the robustness and accuracy of the model in handling anomaly detection tasks, while achieving functionality similar to open-set recognition. To evaluate the proposed LogEDL method, we conduct extensive experiments on three datasets, i.e., HDFS, BGL, and Thunderbird, to detect anomalous log sequences. Experimental results demonstrate that our proposed LogEDL achieves state-of-the-art performance in anomaly detection.

Background: Ice formation on power transmission lines presents significant risks, including structural damage and power outages. Traditional methods for detecting ice on these lines have limitations, particularly in challenging environmental conditions. This study aims to enhance ice detection accuracy by introducing a novel image segmentation and edge detection methodology using improved multi-scale Retinex and advanced morphological operations. Method: The proposed method integrates multi-stage image processing techniques, including image enhancement, grayscale conversion, thresholding, segmentation, object isolation, and edge detection. High-resolution binocular cameras were used to capture images of ice formations on transmission lines. The effectiveness of the method was assessed through a series of metrics, including accuracy, sensitivity, specificity, and precision, and compared with existing methodologies. Results: The proposed method demonstrated superior performance in both ice detection and thickness measurement. The method effectively identified and isolated ice formations under various conditions with an average accuracy of 98.35%, sensitivity of 91.63%, specificity of 99.42%, and precision of 96.03%. Additionally, the analysis of ice thickness measurements further highlighted the method’s accuracy, with a notably low root mean squared error (RMSE) of 1.20 mm and mean absolute error (MAE) of 1.10 mm, along with a strong R-squared value of 0.95. These statistical metrics show that the proposed method not only outperforms previous methods in consistency and alignment with manual measurements but also stands out as the most reliable option for tasks requiring precise measurements, offering significant advancements in accuracy and reliability over existing methodologies. Conclusions: The enhanced image segmentation and edge detection approach provides a more accurate and reliable method for monitoring ice formations on power transmission lines.

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Optical genome mapping (OGM) is an emerging technology that enables genome-wide detection of all classes of SVs at a high resolution and sensitivity. Identification of cryptic SVs leading to gene disruption or predicted novel gene fusions could be important drivers for cancer development and/or portend a prognostic relevance, which could be used to modify the treatment plan. A cohort of 106 consented cases that had a successful OGM analysis performed were included in the study. Demographic, clinical, laboratory and treatment data were collected. Routine diagnostic and prognostic testing were done on the peripheral blood and bone marrow aspirate as indicated. Additional samples of peripheral blood and/or bone marrow were sent for OGM testing. OGM led to a change in risk stratification in 17/66 (25.75%) of patients with hematological malignancies, the majority of these patients (15/66, 22.72%), having their risk stratification upgraded with a resulting change in treatment of 14 patients. This study highlights the ability of OGM to detect rare, cryptic and clinically relevant variants that potentially impact disease diagnosis, risk stratification and actionable treatment targets.

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

Genome-wide association studies (GWAS) have accelerated the exploration of genotype-phenotype associations, facilitating the discovery of replicable genetic markers associated with specific traits or complex diseases. This narrative review explores the statistical methodologies developed using GWAS data to investigate relationships between various phenotypes, focusing on endometrial cancer, the most prevalent gynecological malignancy in developed nations. Advancements in analytical techniques such as genetic correlation, colocalization, cross-trait locus identification, and causal inference analyses have enabled deeper exploration of associations between different phenotypes, enhancing statistical power to uncover novel genetic risk regions. These analyses have unveiled shared genetic associations between endometrial cancer and many phenotypes, enabling identification of novel endometrial cancer risk loci and furthering our understanding of risk factors and biological processes underlying this disease. The current status of research in endometrial cancer is robust; however, this review demonstrates that further opportunities exist in statistical genetic that hold promise for advancing the understanding of endometrial cancer and other complex diseases.

This study focused on the precise detection and concordant analysis of circulating tumor cells (CTCs) to verify the usefulness of CTCs as promising clinical markers. CTCs are traditionally achieved using immune-fluorescence and morphological techniques. By combining two prostate cancer-specific genes (PSA and PSMA) and two epithelial-specific genes (EpCAM and KRT19), the CTC detection efficiency can be enhanced. The detection rates of localized prostate cancer (LPC), locally advanced prostate cancer (LAPC), metastatic hormone-sensitive prostate cancer (mHSPC), and metastatic castration-resistive prostate cancer (mCRPC) were 63.04 % (29/46), 70.59% (34/51), 94.34% (50/53), and 90% (126/140), respectively. Subsequent correlation analysis between the four genes, baseline PSA, and CTC count revealed that only the CTC count correlated with baseline PSA in the localized stages of prostate cancer, whereas all four genes were correlated with baseline PSA and CTC count in the metastatic stages of prostate cancer. The precise detection of CTCs using both numerical and transcriptomic analyses can improve the accuracy of biomarker investigations. This study provides valuable insights into the limitations of serum PSA testing and offers a promising alternative to diagnose and manage prostate cancer via the CTC number and specific genes for prostate cancer.

The World Health Organization (WHO) cancer agency predicts that more than 35 mil-lion cases of will be experienced in 2050, a 77 % increase over the 2022 estimate. Cur-rently, the leading cancer diagnosed cancer are breast, lung and colorectal. There is no standardized tool for cancer diagnosis; initially clinical procedures are guided by the patient´s symptoms and generally involve biochemical blood tests, imaging and biopsy. Label-free nonlinear optical approaches are promising tool for tumor imaging, due to their inherent non-invasive biosafe contrast mechanisms and the ability to monitor collagen-related disorders and metabolic changes during cancer progression. Last ad-vances in nonlinear modalities for tumor imaging are reviewed here. In addition, an application of a blind deconvolution procedure to improve the quality of two-photon images of breast tumor tissues is shown.

This article presents a comparative analysis of three Machine Learning models, namely Logistic Regression, Decision Tree Classifier, and Random Forest Classifier, for prostate cancer detection. The models were trained and evaluated using clinical data, and their performance was assessed using various evaluation metrics. The results show that Logistic Regression achieved the highest accuracy (90%) among the three models, followed by Random Forest Classifier (76.67%) and Decision Tree Classifier (73.33%). Similarly, Logistic Regression demonstrated superior precision (95.65%) and F1 Score (93.62%), indicating its effectiveness in identifying true positive cases. However, the Decision Tree Classifier exhibited higher recall for the negative class (83.33%) compared to the positive class (70.83%), while Random Forest Classifier showed balanced recall for both classes (66.67% for negative and 79.17% for positive). These findings suggest that Logistic Regression outperforms the other models in terms of accuracy and precision, while the Decision Tree Classifier and Random Forest Classifier provide better recall for certain classes. The results highlight the potential of Machine Learning in prostate cancer detection and provide insights for further research and improvement of the models.

Detecting small objects in images poses significant challenges due to their limited pixel representation and the difficulty in extracting sufficient features, often leading to missed or false detections. To address these challenges and enhance detection accuracy, this paper presents an improved small object detection algorithm, CRL-YOLOv5. The proposed approach integrates the CBAM attention mechanism into the C3 module of the backbone network, which enhances the localization accuracy of small objects. Additionally, the Receptive Field Block (RFB) module is introduced to expand the model's receptive field, thereby fully leveraging contextual information. Furthermore, the network architecture is restructured to include an additional detection layer specifically for small objects, allowing for deeper feature extraction from shallow layers. When tested on the VisDrone2019 small object dataset, CRL-YOLOv5 achieved an mAP50 of 39.2%, representing a 5.4% improvement over the original YOLOv5, effectively boosting the detection precision for small objects in images.

Patients with inflammatory bowel diseases (IBD), including both ulcerative colitis (UC) and Crohn's disease (CD), are at a higher risk of developing colorectal cancer (CRC). However, advancements in endoscopic imaging techniques, integrated surveillance programs, and improved medical therapies have led to a decrease in the incidence of CRC among IBD patients. Currently, the management of patients with IBD who have a history of or ongoing active malignancy is an unmet need. This involves balancing the risk of cancer recurrence/progression with the potential exacerbation of IBD if the medications are discontinued. The objective of this review is to provide an updated summary of the epidemiology, causes, risk factors, and surveillance approaches for CRC in individuals with IBD, and to offer practical guidance on managing IBD patients with history of previous or active cancer.

Two-dimensional ultrasound (2D US) is commonly used in clinical settings for its cost-effectiveness and non-invasiveness, but it is limited by spatial orientation and operator dependency. Three-dimensional ultrasound (3D US) overcomes these limitations by adding a third dimension and enhancing integration with other imaging modalities. Advances in deep learning (DL) have further propelled the viability of freehand image-based 3D reconstruction, broadening clinical applications in intraoperative and point-of-care (POC) settings. This review evaluates state-of-the-art freehand 3D US reconstruction methods that eliminate the need for external tracking devices, focusing on experimental setups, data acquisition strategies, and reconstruction methodologies. PubMed, Scopus, and IEEE Xplore were searched for studies since 2014 following PRISMA guidelines, excluding those using additional imaging or tracking systems other than inertial measurement units (IMUs). Fourteen eligible studies were analyzed, showing a shift from traditional speckle decorrelation towards DL-based methods, particularly Convolutional Neural Networks (CNNs). Variability in datasets and evaluation methods hindered a comprehensive quantitative comparison, but notable accuracy improvements were observed with IMUs and integration of contextual and temporal information within CNNs. These advancements enhance freehand 3D US reconstruction feasibility, though variability limits definitive conclusions about the most effective methods. Future research should focus on improving precision in complex trajectories and adaptability across clinical scenarios.

The focus of this work lies in the construction of monitoring system designed in the form of a patch using a long-lasting potentiometric electrolyte concentration sensor from metal electrodes, in a galvanic cell configuration Mg(s)|NaCl(aq)|Cu(s). Initially, a mathematical analysis was conducted on the expected sensor output through the Nernst equation. The experimental phase involved conducting controlled tests in the laboratory using various molar concentrations of sodium chloride (NaCl) in aqueous solution. Results showed that the electrolyte sensor allows for monitoring electrolyte levels in NaCl in the range of 0.02 to 1 M/L, with electrode lifespan exceeding 10 days. On the other hand, when patch is using human sweat during controlled exercise routines, it showed the sensor's capability for monitoring changes in the subjects' hydration levels in real time. The sensor output potential is greater than 1.7 volts when the sensor electrodes are in contact with human sweat, which is equivalent to measuring molar concentrations at normal hydration and moderately high hydration levels. Sensor results indicate that the system can function in a self-powered manner without external batteries. Additionally, the extended lifespan of its electrodes allows for continuous monitoring of imbalances in the human body, showcasing the system capability for long-term health assessment.

Tumor microenvironment including cancer-associated fibroblasts (CAF) has developed as an important target for understanding tumor progression, clinical prognosis and treatment responses of cancer. Cancer cells appear to transform normal fibroblasts (NF) into CAFs involving direct cell-cell communication and epigenetic regulations. This review summarizes the current understanding on miR involvement in cancer cell – tumor environment/stroma communication, transformation of NFs into CAFs, their involved targets and signaling pathways in these interactions; and clinical relevance of CAF-related miR expression profiles. There is evidence that miRs have very similar roles in activating hepatic (HSC) and pancreatic stellate cells (PSC) as part of precancerous fibrotic diseases. In summary, deregulated miRs affect various intracellular functional complexes, such as transcriptional factors, extracellular matrix, cytoskeleton, EMT/MET regulation, soluble factors, tyrosine kinase and G-protein signaling, apoptosis and cell cycle & differentiation, but also formation and composition of the extracellular microenvironment. These processes result in the clinical appearance of desmoplasia involving CAFs and fibrosis characterized by deregulated stellate cells. In addition, modulated release of soluble factors can act as (auto)activating feedback loop for transition of NFs into their pathological counterparts. Furthermore, epigenetic communication between CAFs and cancer cells may confer to cancer specific functional readouts and transition of NF into their pathological counterparts. MiR related epigenetic regulation with many similarities should be considered as key factor in development of cancer and fibrosis specific environment.

In 2022, the new WHO Classification of Endocrine and Neuroendocrine Tumors, Fifth Edition (beta version) (WHO 5th) was published. The importance of understanding the molecular genetics of thyroid tumors as revealed by large-scale genomic analyses such as The Cancer Genome Atlas (TCGA). Consequently, the WHO 5th was fundamentally revised, resulting in a systematic classification based on tumor cell-of-origin and clinical risk. This paper outlines following critical points of the WHO 5th. 1. Genetic mutations in follicular cell-derived neoplasms (FDN) highlight the role of mutations in the MAP kinase pathway, including RET, RAS, and BRAF, as drivers of carcinogenesis. Differentiated thyroid cancers such as follicular thyroid carcinoma (FTC) and papillary thyroid carcinoma (PTC) have specific genetic alterations that correlate with morphological classifications: RAS-like tumors (RLTs) and BRAF p.V600E-like tumors (BLTs), respectively. 2. The Framework for benign lesions have revised. The WHO 5th introduces new categories such as "developmental abnormalities" and "thyroid follicular nodular disease" in benign FDN. 3. Low-Risk Tumors include NIFTP, TT-UMP, and HTT. 4. PTC histological variants are reclassified as "subtypes" in the WHO 5th. 5. The concept of high-grade carcinomas is introduced, encompassing poorly differentiated thyroid carcinoma (PDTC), differentiated high-grade thyroid carcinoma (DHGTC), and high-grade medullary thyroid carcinoma (MTC). 6. Squamous cell carcinoma is included in anaplastic thyroid carcinoma (ATC) in the WHO 5th due to shared genetic and prognostic features. 7. Hürthle cell adenoma/carcinoma is renamed oncocytic thyroid adenoma/carcinoma. 8. Other miscellaneous tumors are classified into salivary gland-type carcinomas of the thyroid, thyroid tumours of uncertain histogenesis, thymic tumours within the thyroid, and embryonal thyroid neoplasms. The WHO 5th thus emphasizes the importance of classifying tumors based on genetic abnormalities together with histomorphology, aiding in accurate pathological diagnosis and treatment selection, including molecular-targeted therapies.

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and the most common form of head and neck cancer, posing significant challenges for disease management. Single-cell RNA sequencing (sc-RNAseq) has emerged as a valuable tool for addressing these challenges by enabling detailed characterization of the tumor microenvironment (TME) at the cellular level. This review assesses the utility of sc-RNAseq in HNSCC research, compiling current strategies employing single-cell technologies. For HNSCC etiology, sc-RNAseq allows for the construction of cellular atlases, characterization of different cell types, and investigation of key genes and processes involved in cancer initiation, development, and progression within the TME. In terms of HNSCC diagnosis and prognosis, the high resolution offered by sc-RNAseq enables the identification of cell type-specific signatures, enhancing prognostic models and disease stratifiers for more accurate patient outcome assessments. Regarding HNSCC treatment, sc-RNAseq provides insights into cellular responses to various treatments, including radiotherapy, chemotherapy, and immunotherapy, contributing to improved patient stratification and personalized treatment strategies. This review highlights the unique contributions of sc-RNAseq to HNSCC research, addressing its cellular and biological complexity, and emphasizes its potential for advancing research and clinical practice in other cancer types.

Predictive biomarkers for immune checkpoint inhibitors (ICI), such as PD-L1 expression (TPS), remain limited in clinical applications. Improved novel ICI predictive biomarkers are urgently needed. We evaluated a live single-cell functional liquid biopsy cytokine profiling platform to track immunotherapy treatment response and outcomes. Peripheral blood mononuclear cell samples of healthy donors and NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-treatment under IRB-approved protocols. Samples were enriched for CD4+ and CD8+ T-lymphocytes and analyzed on the IsoLight platform. The single T-cells were captured in microchambers on IsoCode chips for cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed using the IsoSpeak software, kappa coefficient, and Kaplan-Meier survival plots. We found a significant difference between responders and non-responders in CD8+ T-cells’ changes in overall polyfunctionality and polyfunctional strength index (ΔPSI). ΔPSI score in CD8+ T-cells performed better than PD-L1 TPS and, when combined with PD-L1 TPS, strongly correlated with early ICI treatment response with a kappa coefficient of 1.0 (p=0.003). High CD4+ T-cells ΔPSI predicted a strong trend of improved PFS (3.9-fold) and OS (3-fold). In conclusion, single peripheral T-cell polyfunctionality dynamics analysis is a promising liquid biopsy profiling platform as NSCLC ICI predictive biomarker regardless of oncogene-addiction status.

Gastric cancer has become a serious worldwide health concern, emphasizing the cru-cial importance of early diagnosis measures to improve patient outcomes. While tradi-tional histological image analysis is regarded as the clinical gold standard, it is la-bor-intensive and manual. Recognizing this problem, there has been a rise in interest in using computer-aided diagnostics tools to help pathologists with their diagnostic ef-forts. In particular, deep learning (DL) has emerged as a promising solution in this sector. However, current DL models are still restricted in their ability to extract exten-sive visual characteristics for correct categorization. To tackle this limitation, this study proposes the use of ensemble models, which incorporate the capabilities of sev-eral deep learning architectures and use aggregate knowledge of many models to im-prove classification performance, allowing for more accurate and efficient gastric cancer detection. To see how well these proposed models performed, this study com-pared them to other works, all of which were based on the Gastric Histopathology Sub-size Images Database, a publicly available dataset for gastric cancer. This research demonstrated that the ensemble models achieved high detection accuracy across all sub-databases, with an average accuracy exceeding 99%. Specifically, ResNet50, VGGNet, and ResNet34 performed better than EfficientNet and VitNet. For the 80 × 80 pixel sub-database, ResNet34 exhibited an accuracy of approximately 93%, VGGNet achieved 94%, and the ensemble model excelled with 99%. In the 120 × 120 pixel sub-database, the ensemble model showed 99% accuracy, VGGNet 97%, and ResNet50 approximately 97%. For the 160 × 160 pixel sub-database, the ensemble model again achieved 99% accuracy, VGGNet 98%, ResNet50 98%, and EfficientNet 92%, high-lighting the ensemble model's superior performance across all resolutions. Overall, the ensemble model consistently provided an accuracy of 99% across the three sub-pixel categories. These findings showed that ensemble models may successfully detect criti-cal characteristics from smaller patches and achieve high performance. The findings will help pathologists diagnose gastric cancer using histopathological images, leading to earlier identification and higher patient survival rates.

Recombinant α1-microglobulin (A1M) is proposed as protector during 177Lu-octreotate treatment of neuroendocrine tumors, which is currently limited by bone marrow and renal toxicity. Co-administration of 177Lu-octreotate and A1M could result in a more effective treatment by protecting healthy tissue, but, the radioprotecting action of A1M is not fully understood. The aim of this study was to examine the proteomic response of kidneys and bone marrow early after 177Lu-octreotate and/or A1M administration. Mice were injected with 177Lu-octreotate and/or A1M, while control mice received saline or A1M vehicle solution. Bone marrow, kidney medulla, and kidney cortex were sampled after 24 hours or 7 days. Differential protein expression was analyzed with tandem mass spectrometry. Dosimetric estimation was based on 177Lu activity in kidney. PHLDA3 was the most prominent radiation responsive protein in kidney tissue. In general, no statistically significant difference in expression of radiation-related proteins was observed between the irradiated groups. Most canonical pathways were identified in bone marrow from the 177Lu-octreotate+A1M group. Altogether, tissue-dependent proteomic response followed exposure to 177Lu-octreotate alone or together with A1M. Combining 177Lu-octreotate with A1M did not inhibit the radiation induced protein expression early after exposure, and late effects should be further studied.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

Lung cancer is a prevalent malignancy that impacts individuals of all genders and is often diagnosed late due to delayed symptoms. To catch it early, researchers are developing algorithms to study lung cancer images. One such method uses computer aided detection to classify as benign or malignant from the histopathological images. Standard histopathological images were used from a Lung and Colon Cancer Histopathological Image Dataset (LC25000) which contains two classes of benign and malignant of 5000 each. Images were preprocessed and features extracted using Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). Feature selection methods used are KL Divergence and Invasive Weed Optimization (IWO). Seven different classifiers like SVM, KNN, Random Forest, Decision Tree, Softmax Discriminant, Multilayer Perceptron, and BLDC were used to analyze and classify the images as benign or malignant. Results were compared using standard metrics, and kappa analysis assessed classifier agreement. The Decision Tree Classifier with GWO feature extraction achieved good accuracy of 85.01% without Feature selection and Hyperparameter Tuning approaches. Furthermore, we present a methodology to enhance the accuracy of the classifiers by employing hyperparameter tuning algorithms based on Adam and RAdam. By combining features from GWO and IWO, and using the RAdam algorithm, the Decision Tree classifier achieves the commendable accuracy of 91.57%

Renal cell carcinoma (RCC) represents around 3% of all cancers, within which clear cell RCC (ccRCC) are the most common type (70–75%). The RCC disease regularly progresses asymptomatically and upon presentation is recurrently metastatic, so an early method of detection is necessary. The identification of one or more spe-cific biomarkers measurable in biofluids (i.e urine) by combined approaches could surely be appropriate for this kind of cancer, especially due to easy obtainability by non invasive method. OLR1 is a metabolic gene that encodes for the Lectin-like oxidized low-density lipoprotein re-ceptor-1 (LOX-1), implicated in inflammation, atherosclerosis, ROS and metabolic disor-der-associated carcinogenesis. Specifically, LOX-1 is clearly involved in tumor insurgence and progression of different human cancers. This work reports for the first time the presence of LOX-1 protein in ccRCC urine and its peculiar distribution in tumoral tissues. In parallel, urine samples headspace has been analyzed for the presence of the volatile compounds (VOCs) by SPME-GC/MS and gas sensor array. In particular, it was found by GC/MS analysis that 2-Cyclohexen-1-one,3-methyl-6-(1-methylethyl)- correlates with LOX-1 concentration in urine. Thus, the combined approach of VOCs analysis and protein quantification could led to promis-ing results in terms of diagnostic and prognostic potential for ccRCC tumor.

All types of sports are potential application scenarios for automatic and real-time visual object and event detection. In rink hockey, the popular roller quad skate variant of hockey team sports, it is of great interest to automatically track player’s movements and positions, player’s sticks and, also, making other judgments, such as being able to locate the ball. In this work, we introduce a real-time pipeline composed by an object detection model, created specifically for rink hockey games, followed by a knowledge-based event detection module. Even in the presence of occlusions and quick motions, our deep learning object detection model effectively identifies and tracks, in real-time, important visual elements such as: ball; players; sticks; referees; crowd; goalkeeper; and goal. Using a curated dataset composed by a collection of videos of rink hockey, comprising 2525 annotated frames, we trained and evaluated the algorithm performance and compare it to state of the art object detection techniques. Our object detection model, based on YOLOv7, presents a global accuracy of 80%, and presents a good performance in terms of accuracy and speed, according to our results, making it a good choice for rink hockey applications. In our initial tests, the event detection module successfully detected one important event type in rink hockey games, the occurrence of penalties.