Effect of IL-1ß on the Development of Spermatogenesis In Vitro in Normal and Busulfan-Treated Immature Mice.

Gonadotoxic agents could impair spermatogenesis and may lead to male infertility. The present study aimed to evaluate the effect of IL-1ß 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-1ß 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-1ß 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-1ß compared to cultures treated with IL-1ß from normal mice. Furthermore, addition of IL-1ß 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-1ß 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-1ß to cultures of normal mice did not affect the expression of 3ßHSD 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-1ß could potentiate this development in vitro.

Identification of spermatogenesis in individual seminiferous tubules and testicular tissue of adult normal and busulfan-treated mice employing Raman spectroscopy and principal component analysis.

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.

Infrared spectroscopy-based machine learning algorithms for rapid detection of Klebsiella pneumoniae isolated directly from patients' urine and determining its susceptibility to 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.

Effect of Temperature on the Development of Stages of Spermatogenesis and the Functionality of Sertoli Cells In Vitro.

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 CO2 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.

Monitoring the efficacy of antibiotic therapy in febrile pediatric oncology patients with bacteremia using infrared spectroscopy of white blood cells-based machine learning.

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.

Quick Detection of Proteus and Pseudomonas in Patients' Urine and Assessing Their Antibiotic Susceptibility Using Infrared Spectroscopy and Machine Learning.

Bacterial resistance to antibiotics is a primary global healthcare concern as it hampers the effectiveness of commonly used antibiotics used to treat infectious diseases. The development of bacterial resistance continues to escalate over time. Rapid identification of the infecting bacterium and determination of its antibiotic susceptibility are crucial for optimal treatment and can save lives in many cases. Classical methods for determining bacterial susceptibility take at least 48 h, leading physicians to resort to empirical antibiotic treatment based on their experience. This random and excessive use of antibiotics is one of the most significant drivers of the development of multidrug-resistant (MDR) bacteria, posing a severe threat to global healthcare. To address these challenges, considerable efforts are underway to reduce the testing time of taxonomic classification of the infecting bacterium at the species level and its antibiotic susceptibility determination. Infrared spectroscopy is considered a rapid and reliable method for detecting minor molecular changes in cells. Thus, the main goal of this study was the use of infrared spectroscopy to shorten the identification and the susceptibility testing time of Proteus mirabilis and Pseudomonas aeruginosa from 48 h to approximately 40 min, directly from patients' urine samples. It was possible to identify the Proteus mirabilis and Pseudomonas aeruginosa species with 99% accuracy and, simultaneously, to determine their susceptibility to different antibiotics with an accuracy exceeding 80%.

Studying the Relationship between the Antiviral Activity and the Structure of á¼°-Carrageenan Using Ultrasonication.

á¼°-carrageenan is a linear macroalgal polysaccharide that is well known for its antiviral bioactivity. Although it is considered a candidate for antiviral therapeutics, its application is highly limited due to its low solubility and high viscosity, which lower its adsorption efficiency. With the aim of deriving an active á¼°-carrageenan fragment with an improved adsorption capacity, we studied the effects of ultrasonication on structural changes in á¼°-carrageenan with respect to changes in its bioactivity against herpesviruses. An FTIR analysis revealed that ultrasonication increased the hydrophilicity of á¼°-carrageenan without changing its functional groups, and a rheological analysis demonstrated that it gradually decreased the strength of the polysaccharide gel, which completely lost its gel structure and formed small nanoparticles after 30 min of ultrasonication. Concomitantly with these physicochemical changes, a plaque assay revealed that longer ultrasonication increased the antiviral activity of á¼°-carrageenan against two herpesviruses, namely, HSV-1 and VZV. Finally, we separated the 30-min ultrasonicated á¼°-carrageenan into four fractions and found that fractions with a lower molecular weight were significantly less active against both herpesviruses than those with a higher molecular weight. Our findings show that ultrasonication induces physicochemical changes in á¼°-carrageenan that increase its antiviral bioactivity.

Effect of Granulocyte Colony-Stimulating Factor on the Development of Spermatogenesis in the Adulthood of Juvenile AML Mice Model Treated with Cytarabine.

Pediatric acute myeloid leukemia (AML) generally occurs de novo. The treatment of AML includes cytarabine (CYT) and other medications. The granulocyte-colony stimulating factor (GCSF) is used in the clinic in cases of neutropenia after chemotherapies. We show that the administration of GCSF in combination with CYT in AML-diagnosed mice (AML+CYT+GCSF) extended the survival of mice for additional 20 days. However, including GCSF in all treatment modalities does not affect the testis' weight or the histology of the seminiferous tubules (STs). We show that GCSF does not affect normal ST histology from AML-, CYT-, or (AML+CYT)-treated groups compared to the relevant treated group without GCSF 2, 4, and 5 weeks post-injection. However, when comparing the percentages of normal STs between the AML+CYT+GCSF-treated groups and those without GCSF, we observe an increase of 17%-42% in STs at 4 weeks and 5.5 weeks post-injection. Additionally, we show that the injection of GCSF into the normal, AML-alone, or CYT-alone groups, or in combination with AML, significantly decreases the percentage of STs with apoptotic cells compared to the relevant groups without GCSF and to the CT (untreated mice) only 2 weeks post-injection. We also show that injection of GCSF into the CT group increases the examined spermatogonial marker PLZF within 2 weeks post-injection. However, GCSF does not affect the count of meiotic cells (CREM) but decreases the post-meiotic cells (ACROSIN) within 4 weeks post-injection. Furthermore, GCSF not only extends the survival of the AML+CYT-treated group, but it also leads to the generation of sperm (1.2 ± 0.04 × 106/mL) at 5.5 weeks post-injection. In addition, we demonstrate that the injection of GCSF into the CT group increases the RNA expression level of IL-10 but not IL-6 compared to CT 2 weeks post-treatment. However, the injection of GCSF into the AML-treated group reverses the expression levels of both IL-10 and IL-6 to normal levels compared to CT 2 weeks post-injection. Thus, we suggest that the addition of GCSF to the regimen of AML after CYT may assist in the development of future therapeutic strategies to preserve male fertility in AML prepubertal patients.

Early Detection of Pre-Cancerous and Cancerous Cells Using Raman Spectroscopy-Based Machine Learning.

Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually. Patients with cancer struggle daily due to difficult treatments, pain, and financial and social difficulties. Detecting the disease in its early stages is critical in increasing the likelihood of recovery and reducing the financial burden on the patient and society. Currently used methods for the diagnosis of cancer are time-consuming, producing discomfort and anxiety for patients and significant medical waste. The main goal of this study is to evaluate the potential of Raman spectroscopy-based machine learning for the identification and characterization of precancerous and cancerous cells. As a representative model, normal mouse primary fibroblast cells (NFC) as healthy cells; a mouse fibroblast cell line (NIH/3T3), as precancerous cells; and fully malignant mouse fibroblasts (MBM-T) as cancerous cells were used. Raman spectra were measured from three different sites of each of the 457 investigated cells and analyzed by principal component analysis (PCA) and linear discriminant analysis (LDA). Our results showed that it was possible to distinguish between the normal and abnormal (precancerous and cancerous) cells with a success rate of 93.1%; this value was 93.7% when distinguishing between normal and precancerous cells and 80.2% between precancerous and cancerous cells. Moreover, there was no influence of the measurement site on the differentiation between the different examined biological systems.

Detection of extended-spectrum ß-lactamase-producing bacteria isolated directly from urine by infrared spectroscopy and machine learning.

Resistant bacteria have become one of the leading health threats in the last decades. Extended-spectrum ß-lactamase (ESBL) producing bacteria, including Escherichia (E.) coli and Klebsiella (K.) pneumoniae (the most frequent ones), are a significant class out of all resistant infecting bacteria. Due to the widespread and ongoing development of ESBL-producing (ESBL+) resistant bacteria, many routinely used antibiotics are no longer effective against them. However, an early and reliable ESBL+ bacteria detection method will improve the efficiency of treatment and limit their spread. In this work, we investigated the capability of infrared (IR) spectroscopy based machine learning tools [principal component analysis (PCA) and Random Forest (RF) classifier] for the rapid detection of ESBL+ bacteria isolated directly from patients' urine. For that, we examined 1881 E. coli samples (416 ESBL+ and 1465 ESBL-) and 609 K. pneumoniae samples (237 ESBL+ and 372 ESBL-). All samples were isolated directly from the urine of midstream patients. This study revealed that within 40 min of receiving the patient urine it is possible to determine the infecting bacterium as E. coli or K. pneumoniae with 95% success rate while it was possible to determine the ESBL+E. coli and ESBL+K. pneumoniae with 83% and 78% accuracy rates, respectively.

Instant detection of extended-spectrum ß-lactamase-producing bacteria from the urine of patients using infrared spectroscopy combined with machine learning.

Antibiotics are considered the most effective treatment against bacterial infections. However, most bacteria have already developed resistance to a broad spectrum of commonly used antibiotics, mainly due to their uncontrolled use. Extended-spectrum beta-lactamase (ESBL)-producing bacteria are an essential class of multidrug-resistant (MDR) bacteria. It is of extreme urgency to develop a method that can detect ESBL-producing bacteria rapidly for the effective treatment of patients with bacterial infectious diseases. Fourier transform infrared (FTIR) microscopy is a sensitive method that can rapidly detect cellular molecular changes. In this study, we examined the potential of FTIR spectroscopy-based machine learning algorithms for the rapid detection of ESBL-producing bacteria obtained directly from a patient's urine. Using 591 ESBL-producing and 1658 non-ESBL-producing samples of Escherichia coli (E. coli) and Klebsiella pneumoniae, our results show that the FTIR spectroscopy-based machine learning approach can identify ESBL-producing bacteria within 40 minutes from receiving a patient's urine sample, with a success rate of 80%.

Rapid determination of Proteus mirabilis susceptibility to antibiotics using infrared spectroscopy in tandem with random forest.

Bacterial infections cause serious illnesses that are treated with antibiotics. Currently used methods for detecting bacterial antibiotic susceptibility consume 48-72 h, leading to overuse of antibiotics. Thus, many bacterial species have acquired resistance to a broad range of available antibiotics. There is an urgent need to develop efficient methods for rapid determination of bacterial susceptibility to antibiotics. The combination of machine learning and Fourier-transform infrared (FTIR) spectroscopy has generated a promising diagnostic approach in medicine and biology. Our main goal is to examine the potential of FTIR spectroscopy to determine the susceptibility of urinary tract infection-Proteus mirabilis to a specific range of antibiotics, within about 20 min after 24 h culture and identification. We measured the infrared spectra of 489 different P. mirabilis isolates and used random forest to analyze this spectral database. A classification success rate of ~84% was achieved in differentiating between the resistant and sensitive isolates based on their susceptibility to ceftazidime, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, ciprofloxacin, gentamicin, and sulfamethoxazole antibiotics in a time span of 24 h instead of 48 h.

Fast identification and susceptibility determination of E. coli isolated directly from patients' urine using infrared-spectroscopy and machine learning.

For effective treatment, it is crucial to identify the infecting bacterium at the species level and to determine its antimicrobial susceptibility. This is especially true now, when numerous bacteria have developed multidrug resistance to most commonly used antibiotics. Currently used methods need âˆ¼ 48 h to identify a bacterium and determine its susceptibility to specific antibiotics. This study reports the potential of using infrared spectroscopy with machine learning algorithms to identify E. coli isolated directly from patients' urine while simultaneously determining its susceptibility to antibiotics within âˆ¼ 40 min after receiving the patient's urine sample. For this goal, 1,765 E. coli isolates purified directly from urine samples were collected from patients with urinary tract infections (UTIs). After collection, the samples were tested by infrared microscopy and analyzed by machine learning. We achieved success rates of âˆ¼ 96% in isolate level identification and âˆ¼ 84% in susceptibility determination.

Granulocyte-macrophage colony-stimulating factor (GM-CSF)-induced maturation of spermatogonial cells from prepubertal mice in vitro is enhanced by testosterone.

Spermatogenesis is the complicated process of sperm generation. During this process, spermatogonial cells proliferate and differentiate via meiotic and post-meiotic stages to produce mature sperm. This process is under the regulation of testicular autocrine/paracrine factors. In addition, endocrine factors are crucial to complete spermatogenesis. We aimed to localize granulocyte-macrophage colony-stimulating factor (GM-CSF) and its receptor (GM-CSFR) in testicular cells and further evaluate its involvement in the development of spermatogenesis in vitro. We isolated cells from seminiferous tubule cells of seven-day-old mice and cultured them in vitro using a methylcellulose culture system (MCS), in the presence of GM-CSF and/or testosterone for four weeks. The cells were then examined for markers of different stages of spermatogenesis by immunofluorescence staining and/or qPCR analyses. Our results revealed the presence of GM-CSF and GM-CSFR in testicular cells (premeiotic and meiotic cells as well as somatic cells; Leydig and Sertoli cells). We further demonstrated the development of colonies/spheroids in the MCS which contained pre-meiotic, meiotic, and post-meiotic cells. The addition of GM-CSF to the MCS significantly increased the percentage of pre-meiotic and meiotic cells compared to control. Furthermore, the addition of GM-CSF and testosterone together significantly increased the percentage of cells in the post-meiotic stage compared to the addition of each separately. In conclusion, our results indicate that testicular cells express GM-CSF/GM-CSFR, and that GM-CSF is involved in the development of different stages of spermatogenesis in vitro. Furthermore, testosterone enhances the development of spermatogenic cells and potentiates the effect of GMCSF on the development of post-meiotic cells. These findings provide evidence that GM-CSF and testosterone are involved in the development of spermatogenesis in vitro and in vivo. In brief: Testicular somatic and germ cells express GM-CSF and GM-CSFR. Our study suggests that testicular GM-CSF is involved in the development of spermatogenesis, which is potentiated by testosterone.

Culture-independent susceptibility determination of E. coli isolated directly from patients' urine using FTIR and machine-learning.

One of the most common human bacterial infections is the urinary tract infection (UTI). The main cause of UTI is Escherichia (E.) coli bacteria (∼75%). Because most of the bacteria are resistant to many antibiotics as a result of their indiscriminate overuse, it is extremely important, for effective treatment, to identify the infecting bacteria and to determine, as quickly as possible, their susceptibility to antibiotics. Classical methods require at least 48 hours for determining bacterial susceptibility. In this study, 1798 E. coli isolates from different UTIs were isolated directly from patients' urine, measured by Fourier transform infrared (FTIR) microscopy and analyzed by machine learning algorithms for simultaneous identification and susceptibility determination within 40 minutes since receiving the urine samples. Our results show that it is possible to identify the bacteria at the species level with an accuracy of ∼95% and to determine their susceptibility to different antibiotics with an accuracy ranging from 75% to 83%.

Determining the expression levels of CSF-1 and OCT4, CREM-1, and protamine in testicular biopsies of adult Klinefelter patients: Their possible correlation with spermatogenesis.

Klinefelter syndrome (KS) is the most prevalent genetic disorder of infertile males. This study aimed to determine in Klinefelter patients (KS) the expression levels of spermatogenic markers and testicular growth factors that might predict spermatogenesis based on conventional testicular sperm extraction (TESE). The expression levels of the pre-meiotic (OCT4, CD9, GFR-α1, α-6-INTEGRIN, SALL4, C-KIT), meiotic (CREM-1), and post-meiotic (protamine) markers, as well as the colony stimulating factor-1 (CSF-1) were examined in testicular biopsies with and without mature sperm of KS and normal karyotype of azoospermic patients (AZO) with complete spermatogenesis. In the biopsies of AZO, the expression levels (fold of expression compared to the PPI of the same sample) of OCT4 were 9.68± 7.93, CREM 42.78± 28.22, CSF-1 3.07 ± 3.19, and protamine 78498.12 ± 73214.40. Biopsies from KS included 7 with sperm and 17 without sperm. Among the biopsies with sperm, the expression levels of OCT4 were 7.27± 9.29, CREM 3.13± 7.89, CSF-1 35.5 ± 48.01, and protamine 902.97 ± 2365.92. In 14 biopsies without sperm, we found low expression levels of OCT4, CREM and CSF-1, and no expression of protamine. However, in three of the biopsies without sperm that highly expressed OCT4 and CSF-1, the expression levels of CREM-1 and protamine were high. These results may be used for further consulting with patients considering repeating conventional TESE or micro TESE and cryopreservation for possible future in-vitro spermatogenesis.

Perfusion in Organ-on-Chip Models and Its Applicability to the Replication of Spermatogenesis In Vitro.

Organ/organoid-on-a-chip (OoC) technologies aim to replicate aspects of the in vivo environment in vitro, at the scale of microns. Mimicking the spatial in vivo structure is important and can provide a deeper understanding of the cell-cell interactions and the mechanisms that lead to normal/abnormal function of a given organ. It is also important for disease models and drug/toxin testing. Incorporating active fluid flow in chip models enables many more possibilities. Active flow can provide physical cues, improve intercellular communication, and allow for the dynamic control of the environment, by enabling the efficient introduction of biological factors, drugs, or toxins. All of this is in addition to the fundamental role of flow in supplying nutrition and removing waste metabolites. This review presents an overview of the different types of fluid flow and how they are incorporated in various OoC models. The review then describes various methods and techniques of incorporating perfusion networks into OoC models, including self-assembly, bioprinting techniques, and utilizing sacrificial gels. The second part of the review focuses on the replication of spermatogenesis in vitro; the complex process whereby spermatogonial stem cells differentiate into mature sperm. A general overview is given of the various approaches that have been used. The few studies that incorporated microfluidics or vasculature are also described. Finally, a future perspective is given on elements from perfusion-based models that are currently used in models of other organs and can be applied to the field of in vitro spermatogenesis. For example, adopting tubular blood vessel models to mimic the morphology of the seminiferous tubules and incorporating vasculature in testis-on-a-chip models. Improving these models would improve our understanding of the process of spermatogenesis. It may also potentially provide novel therapeutic strategies for pre-pubertal cancer patients who need aggressive chemotherapy that can render them sterile, as well asfor a subset of non-obstructive azoospermic patients with maturation arrest, whose testes do not produce sperm but still contain some of the progenitor cells.

Effect of Chemotherapy Cytarabine and Acute Myeloid Leukemia on the Development of Spermatogenesis at the Adult Age of Immature Treated Mice.

Acute myeloid leukemia (AML) accounts for around 20% of diagnosed childhood leukemia. Cytarabine (CYT) is involved in the AML treatment regimen. AML and CYT showed impairment in spermatogenesis in human and rodents in adulthood. We successfully developed an AML disease model in sexually immature mice. Monocytes and granulocytes were examined in all groups: untreated control, AML alone, CYT alone and AML+CYT (in combination). There was a significant increase in the counts of monocytes and granulocytes in the AML-treated immature mice (AML) compared to the control, and AML cells were demonstrated in the blood vessels of the testes. AML alone and CYT alone impaired the development of spermatogenesis at the adult age of the AML-treated immature mice. The damage was clear in the structure/histology of their seminiferous tubules, and an increase in the apoptotic cells of the seminiferous tubules was demonstrated. Our results demonstrated a significant decrease in the meiotic/post-meiotic cells compared to the control. However, CYT alone (but not AML) significantly increased the count of spermatogonial cells (premeiotic cells) that positively stained with SALL4 and PLZF per tubule compared to the control. Furthermore, AML significantly increased the count of proliferating spermatogonial cells that positively stained with PCNA in the seminiferous tubules compared to the control, whereas CYT significantly decreased the count compared to the control. Our result showed that AML and CYT affected the microenvironment/niche of the germ cells. AML significantly decreased the levels growth factors, such as SCF, GDNF and MCSF) compared to control, whereas CYT significantly increased the levels of MCSF and GDNF compared to control. In addition, AML significantly increased the RNA expression levels of testicular IL-6 (a proinflammatory cytokine), whereas CYT significantly decreased testicular IL-6 levels compared to the control group. Furthermore, AML alone and CYT alone significantly decreased RNA expression levels of testicular IL-10 (anti-inflammatory cytokine) compared to the control group. Our results demonstrate that pediatric AML disease with or without CYT treatment impairs spermatogenesis at adult age (the impairment was more pronounced in AML+CYT) compared to control. Thus, we suggest that special care should be considered for children with AML who are treated with a CYT regimen regarding their future fertility at adult age.

Testis on a chip-a microfluidic three-dimensional culture system for the development of spermatogenesisin-vitro.

This research presents a novel testis-on-a-chip (ToC) platform. Testicular cells are enzymatically isolated from the seminiferous tubules of sexually immature mice, seeded in a methylcellulose gel and cultured in a microfluidic chip. The unique design sandwiches the soft methylcellulose between stiffer agar support gels. The cells develop into spheroids continuing to proliferate and differentiate. After seven weeks of culture the cells have over 95% viability. Confocal microscopy of the developed spheroids reveals a structure containing the various stages of spermatogenesis up to and including meiosis II: premeiotic, meiotic and post-meiotic germ cells. The spheroid structure also contains the supporting Sertoli and peritubular cells. The responsiveness of the system to the addition of testosterone and retinoic acid to the culture medium during the experiment was also investigated. As a benchmark, the ToC is compared to a conventional three-dimensional methylcellulose cell culture system in a well plate. Analysis via fluorescence-activated cell sorting shows more haploid cells in the chip as compared to the plates. Immunofluorescence staining after seven weeks of culture shows more differentiated cells in the chip as compared to the well plate. This demonstrates the feasibility of our platform as well as its advantages. This research opens new horizons for the study and realization of spermatogenesisin-vitro. It can also enable the implementation of microfluidic technologies in future therapeutic strategies for pre-pubertal male fertility preservation and adults with maturation arrest. Lastly, it can serve as a platform for drug and toxin testing.

Infra-red spectroscopy combined with machine learning algorithms enables early determination of Pseudomonas aeruginosa's susceptibility to antibiotics.

Pseudomonas (P.) aeruginosa is a bacterium responsible for severe infections that have become a real concern in hospital environments. Nosocomial infections caused by P. aeruginosa are often hard to treat because of its intrinsic resistance and remarkable ability to acquire further resistance mechanisms to multiple groups of antimicrobial agents. Thus, rapid determination of the susceptibility of P. aeruginosa isolates to antibiotics is crucial for effective treatment. The current methods used for susceptibility determination are time-consuming; hence the importance of developing a new method. Fourier-transform infra-red (FTIR) spectroscopy is known as a rapid and sensitive diagnostic tool, with the ability to detect minor abnormal molecular changes including those associated with the development of antibiotic- resistant bacteria. The main goal of this study is to evaluate the potential of FTIR spectroscopy together with machine learning algorithms, to determine the susceptibility of P. aeruginosa to different antibiotics in a time span of ∼20 min after the first culture. For this goal, 590 isolates of P. aeruginosa, obtained from different infection sites of various patients, were measured by FTIR spectroscopy and analyzed by machine learning algorithms. We have successfully determined the susceptibility of P. aeruginosa to various antibiotics with an accuracy of 82-90%.