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Cryopreservation is a useful approach to preserve male fertility for assisted reproduction technique and other evaluations. In spite of extensive development in the cryopreservation field, there are biological and biochemical points including DNA fragmentation and antioxidant which should be illuminated to preserve fertility in safe form. Several molecular markers such as coding and noncoding RNAs are transferred from spermatozoa into oocyte via fertilization. These biomarkers affect fertility potential during the cryopreservation. Despite its impact, sperm cryopreservation has some destructive effect including loss of sperm motility and viability, acrosomal damage, mitochondrial membrane depolarization, plasma membrane permeability alteration even nuclear, and DNA damage. There is a growing concern about the impact of sperm cryopreservation on biological factors which can interrupt successful fertility procedures such as in vitro fertilization. Additionally, cryo-damage can decrease embryonic development extent. Promoting cryopreservation method via investigating the wide range of non-invasive factors may be increasingly important to have access to safe approach of freezing. Therefore, the aim of this study is the assessment of biological factors which can penetrate the fertility potential during the freezing procedure, explicate innovative methods in fertility preservation.

Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with rising incidence and with 5-years overall survival of less than 8%. PDAC creates an immune-suppressive tumor microenvironment to escape immune-mediated eradication. Regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSC) are critical components of the immune-suppressive tumor microenvironment. Shifting from tumor escape or tolerance to elimination is the major challenge in the treatment of PDAC. Results In a mathematical model, we combine distinct treatment modalities for PDAC, including 5-FU chemotherapy and anti- CD25 immunotherapy to improve clinical outcome and therapeutic efficacy. To address and optimize 5-FU and anti- CD25 treatment (to suppress MDSCs and Tregs, respectively) schedule in-silico and simultaneously unravel the processes driving therapeutic responses, we designed an in vivo calibrated mathematical model of tumor-immune system (TIS) interactions. We designed a user-friendly graphical user interface (GUI) unit which is configurable for treatment timings to implement an in-silico clinical trial to test different timings of both 5-FU and anti- CD25 therapies. By optimizing combination regimens, we improved treatment efficacy. In-silico assessment of 5-FU and anti- CD25 combination therapy for PDAC significantly showed better treatment outcomes when compared to 5-FU and anti- CD25 therapies separately. Due to imprecise, missing, or incomplete experimental data, the kinetic parameters of the TIS model are uncertain that this can be captured by the fuzzy theorem. We have predicted the uncertainty band of cell/cytokines dynamics based on the parametric uncertainty, and we have shown the effect of the treatments on the displacement of the uncertainty band of the cells/cytokines. We performed global sensitivity analysis methods to identify the most influential kinetic parameters and simulate the effect of the perturbation on kinetic parameters on the dynamics of cells/cytokines. Conclusion Our findings outline a rational approach to therapy optimization with meaningful consequences for how we effectively design treatment schedules (timing) to maximize their success, and how we treat PDAC with combined 5-FU and anti- CD25 therapies. Our data revealed that a synergistic combinatorial regimen targeting the Tregs and MDSCs in both crisp and fuzzy settings of model parameters can lead to tumor eradication.

miRNAs (MicroRNAs), known as noncoding and important endogenous factors regulating the expression protein‐coding genes, are vital regulators in each biological process. Thus, this study aims to explore the key role of four microRNAs in regulating the spermatogenesis. To conduct this experiment, 55 infertile and fertile men provided the study with the sperm and testicular tissue samples. To study the spermatozoa in terms of the morphology, Diff‐Quick was applied. Then, quantitative real‐time polymerase chain reaction (RT‐PCR) was conducted on samples. Our data indicated that in contrast to the miR‐15b, significant increasing of miR‐383 and miR‐122 occurred in both severe oligoasthenoteratozoospermia (SOAT) and moderate oligoasthenoteratozoospermia (MOAT) compared to normal sperm group (N). In addition, it was observed that miR‐15b and miR‐122 increased in patients with nonobstructive azoospermia (NOA) compared with obstructive azoospermia (OA) group. Expression levels of target genes including P53, CASPASE‐9 and CYCLIN D1 underwent principle changes according to miRNAs expression level. Our finding indicated that miRNAs had essential role in the regulation of spermatogenesis, and their expression altering was associated with sperm abnormalities. Thus, microRNAs can be introduced as useful biomarkers to determine male infertility reasons to choose the effective treatment.

Objectives: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomic structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal. Methods: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions. Results: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3% and a normalised surface distance (NSD) of 98.2 ± 2.2%. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4% and a NSD of 98.4 ± 3.6%. Conclusions: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software.Clinical Significance: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.

The repair and regeneration of articular cartilage represent important challenges for orthopedic investigators and surgeons worldwide due to its avascular, aneural structure, cellular arrangement, and dense extracellular structure. Although abundant efforts have been paid to provide tissue-engineered grafts, the use of therapeutically cell-based options for repairing cartilage remains unsolved in the clinic. Merging a clinical perspective with recent progress in nanotechnology can be helpful for developing efficient cartilage replacements. Nanomaterials, < 100 nm structural elements, can control different properties of materials by collecting them at nanometric sizes. The integration of nanomaterials holds promise in developing scaffolds that better simulate the extracellular matrix (ECM) environment of cartilage to enhance the interaction of scaffold with the cells and improve the functionality of the engineered-tissue construct. This technology not only can be used for the healing of focal defects but can also be used for extensive osteoarthritic degenerative alterations in the joint. In this review paper, we will emphasize the recent investigations of articular cartilage repair/regeneration via biomaterials. Also, the application of novel technologies and materials is discussed.

Reinforced concrete remains integral to modern infrastructure, yet traditional designs, relying on longitudinal reinforcing bars and stirrups, face limitations in adaptability and performance optimization. This study explores the integration of auxetic structures with negative Poisson ratios (NPRs) as reinforcement for concrete, leveraging advances in additive manufacturing to achieve enhanced mechanical properties. Three auxetic geometries, brick‐and‐mortar, bowtie, and tubular, are fabricated using aluminum, stainless steel, and polylactic acid (PLA) and are evaluated experimentally and numerically. Stainless steel tubular structures achieve a record compressive strength of 233 MPa, exceeding high‐performance fiber‐reinforced concrete (HPFRC) at similar reinforcement volumes. In particular, auxetic aluminum tubular reinforcements demonstrate a specific compressive strength of 149 kJ g−1, equivalent to steel fiber reinforced concrete. Bowtie geometries improve toughness by redistributing stress, and tubular structures exhibit superior energy absorption and load redistribution. Finite element simulations reveal stress concentration mitigation and delay crack propagation, corroborating the experimental results. These findings highlight the significant impact of reinforcement geometry on structural performance and demonstrate that auxetic reinforcements can outperform conventional designs in strength, stiffness, and energy dissipation. This work establishes auxetic designs as a viable and promising strategy for next‐generation reinforced concrete systems aimed at improving resilience and mechanical efficiency. The schematic illustrates auxetic reinforcement geometries and fabrication materials. Results show enhanced strength, stiffness, and energy absorption, with tubular stainless steel achieving the highest performance, highlighting the critical role of reinforcement geometry in next‐generation high‐performance concrete structures.

Introduction Telomeres protect the ends of chromosomes, and shorter leukocyte telomeres are associated with major group diseases. Maternal psychological stress may be related to the shortening of telomeres in infants. This systematic review and meta-analysis set out to consolidate the varying effect sizes found in studies of maternal psychological stress and telomere length (TL) in newborns and identify moderators of the relationship between stress during pregnancy and newborn TL. Methods Our systematic review was registered in Prospero. Six databases (PubMed, Scopus, Embase, PsycINFO, Web of Science, and CINAHL Complete) were searched for records in English from inception to February 10, 2023. Observational studies were included that measured the relationship of psychological stress of the mother during pregnancy on the TL of the newborn. The Newcastle–Ottawa quality assessment scale was used to assess the quality of the included studies. A random-effect model was selected. Statistical analysis performed by Stata software version 17. Results Eight studies were included for qualitative and four for quantitative analysis. There was an inverse statistically significant relationship between maternal stress and newborn TL; A one score increase in maternal psychological stress resulted in a 0.04 decrease in the TL of the newborn ( B  =  -0.04, 95% CI  =  [-0.08, 0.00], p  =  0.05 ). Selectivity analysis showed that the pooled effect size was sensitive to one study; After removing this study, the pooled effect size remained significant ( B  =  -0.06, 95% CI  =  [-0. 10, -0.02], p  <  0.001). Conclusion Physiological and environmental factors can significantly affect the TL of newborns. Our results support a significant impact of maternal psychological stress on the TL of a newborn. This association demonstrates the significance of stress in influencing the telomere length, which can be a contributing factor in the infant’s future. Therefore, recognizing this association is crucial for understanding and addressing potential health risks and necessitates the need for additional future studies to validate our findings.

A methanol poisoning outbreak occurred in Iran during the initial months of coronavirus disease 2019 (COVID-19) pandemic. We aimed to evaluate the epidemiology of the outbreak in terms of hospitalizations and deaths. A cross-sectional linkage study was conducted based on the hospitalization data collected from thirteen referral toxicology centers throughout Iran as well as mortality data obtained from the Iranian Legal Medicine Organization (LMO). Patient data were extracted for all cases aged > 19 years with toxic alcohol poisoning during the study period from February until June 2020. A total of 795 patients were hospitalized due to methanol poisoning, of whom 84 died. Median [interquartile ratio; IQR] age was 32 [26, 40] years (range 19–91 years). Patients had generally ingested alcohol for recreational motives (653, 82.1%) while 3.1% (n = 25) had consumed alcohol-based hand sanitizers to prevent or cure COVID-19 infection. Age was significantly lower in survivors than in non-survivors (P < 0.001) and in patients without sequelae vs. with sequelae (P = 0.026). Twenty non-survivors presented with a Glasgow Coma Scale (GCS) score > 8, six of whom were completely alert on presentation to the emergency departments. The time from alcohol ingestion to hospital admission was not significantly different between provinces. In East Azerbaijan province, where hemodialysis was started within on average 60 min of admission, the rate of sequelae was 11.4% (compared to 19.6% average of other provinces)—equivalent to a reduction of the odds of sequelae by 2.1 times [95% CI 1.2, 3.7; p = 0.009]. Older patients were more prone to fatal outcome and sequelae, including visual disturbances. Early arrival at the hospital can facilitate timely diagnosis and treatment and may reduce long-term morbidity from methanol poisoning. Our data thus suggest the importance of raising public awareness of the risks and early symptoms of methanol intoxication.

Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated). We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating on parameters that have more direct policy implications, these potentially automated approaches allow methodological standardization across similar comparativeness effectiveness studies.