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In studying the molecular underpinning of spermatogenesis, we expect to understand the fundamental biological processes better and potentially identify genes that may lead to novel diagnostic and therapeutic strategies toward precision medicine in male infertility. In this review, we emphasized our perspective that the path forward necessitates integrative studies that rely on complementary approaches and types of data. To comprehensively analyze spermatogenesis, this review proposes four axes of integration. First, spanning the analysis of spermatogenesis in the healthy state alongside pathologies. Second, the experimental analysis of model systems (in which we can deploy treatments and perturbations) alongside human data. Third, the phenotype is measured alongside its underlying molecular profiles using known markers augmented with unbiased profiles. Finally, the testicular cells are studied as ecosystems, analyzing the germ cells alongside the states observed in the supporting somatic cells. Recently, the study of spermatogenesis has been advancing using single-cell RNA sequencing, where scientists have uncovered the unique stages of germ cell development in mice, revealing new regulators of spermatogenesis and previously unknown cell subtypes in the testis. An in-depth analysis of meiotic and postmeiotic stages led to the discovery of marker genes for spermatogonia, Sertoli and Leydig cells and further elucidated all the other germline and somatic cells in the testis microenvironment in normal and pathogenic conditions. The outcome of an integrative analysis of spermatogenesis using advanced molecular profiling technologies such as scRNA-seq has already propelled our biological understanding, with additional studies expected to have clinical implications for the study of male fertility. By uncovering new genes and pathways involved in abnormal spermatogenesis, we may gain insights into subfertility or sterility.

The present study aims to identify spermatogenesis in testicular seminiferous tubules (ST) and testicular tissue of adult normal and busulfan-treated mice utilizing PCA and Raman spectroscopy. Raman measurements were conducted on single tubules and testes samples from adult and immature mice, comparing them with those from busulfan-treated adult mice, with validation through histological examination. The analysis revealed a higher signal variability (30 %-40 % at the peaks), prompting scrutiny of individual Raman spectra as a means of spermatogenesis measurement. However, principal component analysis (PCA) demonstrated significant cluster separation between the ST of mature and immature mice. Similar investigations were performed to compare ST from normal mature mice and those from busulfan-treated (BS-treated) mature mice, revealing substantial separation along PC1 and PC2 for all comparison sets. Additionally, comparing testicular samples from mature and immature mice revealed distinct separation in PCA. The study concludes that the combined approach of PCA and Raman spectroscopy proves to be a noninvasive and potentially valuable method for identifying spermatogenesis in seminiferous tubules and testicular samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Rapid testing of bacteria for antibiotic susceptibility is essential for effective treatment and curbing the emergence of multidrug-resistant bacteria. The misuse of antibiotics, coupled with the time-consuming classical testing methods, intensifies the threat of antibiotic resistance, a major global health concern. In this study, employing infrared spectroscopy-based machine learning techniques, we significantly shortened the time required for susceptibility testing to 10 hours, a significant improvement from the 24 hours in our previous studies as well as the conventional methods that typically take at least 48 hours. This remarkable reduction in turnaround time (from 48 hours to 10 hours), achieved by minimizing the culturing period, offers a game-changing advantage for clinical applications. Our study involves a dataset comprising 400 bacterial samples (200 E. coli , 100 Klebsiella pneumoniae , and 100 Pseudomonas aeruginosa ) with an impressive 96% accuracy in the taxonomic classification at the species level and up to 82% accuracy in bacterial susceptibility to various antibiotics.

Among the most prevalent and detrimental bacteria causing urinary tract infections (UTIs) is Klebsiella (K.) pneumoniae. A rapid determination of its antibiotic susceptibility can enhance patient treatment and mitigate the spread of resistant strains. In this study, we assessed the viability of using infrared spectroscopy-based machine learning as a rapid and precise approach for detecting K. pneumoniae bacteria and determining its susceptibility to various antibiotics directly from a patient's urine sample. In this study, 2333 bacterial samples, including 636 K. pneumoniae were investigated using infrared micro-spectroscopy. The obtained spectra (27996spectra) were analyzed with XGBoost classifier, achieving a success rate exceeding 95 % for identifying K. pneumoniae. Moreover, this method allows for the simultaneous determination of K. pneumoniae susceptibility to various antibiotics with sensitivities ranging between 74 % and 81 % within approximately 40 min after receiving the patient's urine sample., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Gonadotoxic agents could impair spermatogenesis and may lead to male infertility. The present study aimed to evaluate the effect of IL-1β on the development of spermatogenesis from cells isolated from seminiferous tubules (STs) of normal and busulfan-treated immature mice in vitro. Cells were cultured in a 3D in vitro culture system for 5 weeks. We examined the development of cells from the different stages of spermatogenesis by immunofluorescence staining or qPCR analyses. Factors of Sertoli and Leydig cells were examined by qPCR analysis. We showed that busulfan (BU) treatment significantly reduced the expression of testicular IL-1β in the treated mice compared to the control group (CT). Cultures of cells from normal and busulfan-treated immature mice induced the development of pre-meiotic (Vasa), meiotic (Boule), and post-meiotic (acrosin) cells. However, the percentage of developed Boule and acrosin cells was significantly lower in cultures of busulfan-treated mice compared to normal mice. Adding IL-1β to both cultures significantly increased the percentages of Vasa, Boule, and acrosin cells compared to their controls. However, the percentage of Boule and acrosin cells was significantly lower from cultures of busulfan-treated mice that were treated with IL-1β compared to cultures treated with IL-1β from normal mice. Furthermore, addition of IL-1β to cultures from normal mice significantly increased only the expression of androgen receptor and transferrin but no other factors of Sertoli cells compared to their CT. However, the addition of IL-1β to cultures from busulfan-treated mice significantly increased only the expression of androgen-binding protein and the FSH receptor compared to their CT. Adding IL-1β to cultures of normal mice did not affect the expression of 3βHSD compared to the CT, but it significantly reduced its expression in cultures from busulfan-treated mice compared to the CT. Our findings demonstrate the development of different stages of spermatogenesis in vitro from busulfan-treated mice and that IL-1β could potentiate this development in vitro.

Bacteremia refers to the presence of bacteria in the bloodstream, which can lead to a serious and potentially life-threatening condition. In oncology patients, individuals undergoing cancer treatment have a higher risk of developing bacteremia due to a weakened immune system resulting from the disease itself or the treatments they receive. Prompt and accurate detection of bacterial infections and monitoring the effectiveness of antibiotic therapy are essential for enhancing patient outcomes and preventing the development and dissemination of multidrug-resistant bacteria. Traditional methods of infection monitoring, such as blood cultures and clinical observations, are time-consuming, labor-intensive, and often subject to limitations. This manuscript presents an innovative application of infrared spectroscopy of leucocytes of pediatric oncology patients with bacteremia combined with machine learning to diagnose the etiology of infection as bacterial and simultaneously monitor the efficacy of the antibiotic therapy in febrile pediatric oncology patients with bacteremia infections. Through the implementation of effective monitoring, it becomes possible to promptly identify any indications of treatment failure. This, in turn, indirectly serves to limit the progression of antibiotic resistance. The logistic regression (LR) classifier was able to differentiate the samples as bacterial or control within an hour, after receiving the blood samples with a success rate of over 95 %. Additionally, initial findings indicate that employing infrared spectroscopy of white blood cells (WBCs) along with machine learning is viable for monitoring the success of antibiotic therapy. Our follow up results demonstrate an accuracy of 87.5 % in assessing the effectiveness of the antibiotic treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Spermatogenesis is the process of proliferation and differentiation of spermatogonial cells to meiotic and post-meiotic stages and sperm generation. Normal spermatogenesis occurs in vivo at 34 °C to 35 °C, and high temperatures are known to cause male infertility. The aim of the present study was to examine the effect of temperature (35 °C compared to 37 °C) on the viability/apoptosis of developed cells, on the development of different stages of spermatogenesis in 3D in vitro culture conditions, and the functionality of Sertoli cells under these conditions. We used isolated cells from seminiferous tubules of sexually immature mice. The cells were cultured in methylcellulose (as a three-dimensional (3D) in vitro culture system) and incubated in a CO 2 incubator at 35 °C or 37 °C. After two to six weeks, the developed cells and organoids were collected and examined for cell viability and apoptosis markers. The development of different stages of spermatogenesis was evaluated by immunofluorescence staining or qPCR analysis using specific antibodies or primers, respectively, for cells at each stage. Factors that indicate the functionality of Sertoli cells were assessed by qPCR analysis. The developed organoids were examined by a confocal microscope. Our results show that the percentages and/or the expression levels of the developed pre-meiotic, meiotic, and post-meiotic cells were significantly higher at 35 °C compared to those at 37 °C, including the expression levels of the androgen receptor, the FSH receptor, transferrin, the androgen-binding protein (ABP), and the glial-derived nerve growth factor (GDNF) which were similarly significantly higher at 35 °C than at 37 °C. The percentages of apoptotic cells (according to acridine orange staining) and the expression levels of BAX, FAS, and CASPAS 3 were significantly higher in cultures incubated at 37 °C compared to those incubated at 35 °C. These findings support the in vivo results regarding the negative effect of high temperatures on the process of spermatogenesis and suggest a possible effect of high temperatures on the viability/apoptosis of spermatogenic cells. In addition, increasing the temperature in vitro also impaired the functionality of Sertoli cells. These findings may deepen our understanding of the mechanisms behind optimal conditions for normal spermatogenesis in vivo and in vitro.