Osteoarthritis (OA) is a major public and animal health challenge with significant economic consequences. Cartilage degradation plays a critical role in the initiation and progression of degenerative joint diseases, such as OA. Mesenchymal stem cells (MSCs) have become increasingly popular in the field of cartilage regeneration due to their promising results. The objective of this preclinical study was to evaluate the regenerative effects of mesenchymal stem cells (MSCs) in the repair of knee cartilage defects using a porcine model. Seven healthy LYD breed white pigs, aged 9–10 weeks and weighing approximately 20 ± 3 kg, were used in the experimental protocol. Full-thickness defects measuring 8 mm in diameter and 5 mm in depth were induced in the lateral femoral condyle of the posterior limbs in both knee joints using a sterile puncture technique while the knee was maximally flexed. Following a 1-week induction phase, the pig treatment groups received a 0.3 million/kg MSC transplant into the damaged knee region, while the placebo group received a control solution as a treatment. Magnetic resonance imaging (MRI), computerized tomography (CT), visual macroscopic examination, histological analysis, and cytokine concentration analysis were used to assess cartilage regeneration. The findings revealed that human adipose-derived mesenchymal stem cells (hADSCs) were more effective in repairing cartilage than pig umbilical cord-derived mesenchymal stem cells (pUCMSCs). These results suggest that MSC-based treatments hold promise as a treatment option for cartilage repair, which aid in the treatment of OA. However, further studies with larger sample sizes and longer follow-up periods are required to fully demonstrate the safety and efficacy of these therapies in both animals and humans. Knee osteoarthritis (OA) is a degenerative joint disease that affects both humans and animals, resulting in significant pain and disability with economic loss ,2,3. TheThe pathogenesis of knee osteoarthritis is significantly influenced by cartilage degradation, which plays a crucial role in disease initiation and progression. Consequently, there has been considerable research focused on investigating strategies for cartilage repair and regeneration in the context of knee OA ,15. The Despite significant research efforts, knee osteoarthritis remains a major public health challenge with no known cure. Current treatment options, such as pain management and joint replacement, only offer temporary relief and do not address the underlying cartilage loss and joint degeneration . FurtherThe current research on the effect of mesenchymal stem cells on cartilage regeneration in pigs is limited, necessitating additional studies employing large-animal models to completely investigate the safety and efficiency of MSCs in a preclinical setting . The aimThe research is organized as follows to provide a comprehensive structural overview of our study: an introduction section that includes a detailed literature review and background information, a materials and methods section that outlines the reagents and equipment used in the experimental design, a results section that presents our findings using tables, graphs, and microscopy images, and a discussion section that explains the theoretical basis of our results.The experiment titled “Regenerative effect of mesenchymal stem cell on knee cartilage damage in a porcine model” was conducted from 2022 to 2023 at the National Pingtung University of Science and Technology (NPUST), Taiwan (22°38′16.19″ N and 120°35′26.39″ E). A schematic illustration of the experimental design is presented , with th3 fragments. These fragments were placed on 10 cm culture dishes and cultured in alpha-MEM  supplemented with 5% UltraGROTM  and antibiotics . The cultures were incubated at 37 degrees Celsius in a humidified atmosphere with 5% CO2. Every 3–4 days, new media was introduced. When the cultures reached confluence, they were washed with DPBS, harvested with 0.05% TrypLE , and transferred to fresh 10 cm culture dishes at a plating density of 3–6 × 103 cells per cm2 for continued growth. Finally, the MSCs were cryopreserved in culture media containing 10% DMSO in a vapor phase liquid nitrogen tank at −190 °C using a control rate freezer . Both hADSC and pUCMSC cells from passage three were used for the experiment. The MSCs were cultured in the BIONET Lab  under Good Manufacturing Practice conditions. They reported that the expanded cells were then evaluated for number, viability, purity, and identity. Before injection, MSCs were counted using a hemocytometer and loaded into a syringe.MSCs were funded by Bionet company, . They were unable to reveal the specific culture medium chosen for the study due to its unique element, which was a valuable trade secret for the company. With minor modifications to the protocol , human aThe research was performed in the animal research laboratory of National Pingtung University of Science and Technology (NPUST). White LYD  pigs (n = 7) body weight of 20 to 25 kg with age group 9–10 weeks were used. Pigs were purchased from a commercial farm near NPUST and placed at the NPUST positive control animal facility room. When performing this study at National Pingtung University of Science and Technology, International Animal Care and Use Committee (IACUC) protocols were followed. The International Animal Care and Use Committee (IACUC) approved the animal research and issued an IACUC permit number (NPUST-110-079). Because the ethical care of animals is of the highest concern, all pre-operative, surgical, and post-operative procedures were carried out in compliance with IACUC standards. The pigs were allowed to become acclimated to their surroundings prior to the commencement of the experiment. The pigs had unrestricted access to food and water and were reared in a controlled environment with a 12-h/12-h light/dark cycle at 23 ± 2 °C with relative humidity of 65 ± 5%. All pigs were physically evaluated to ensure their safety and well-being, and were immediately ear tagged with a specific number for identification purposes during this study .In this study, we analyzed the effectiveness of the healing of cartilage using straightforward experimental designs. Twelve knees of seven pigs were randomly assigned to four groups  Figure . In the This study was carried out in three stages, employing a consistent methodology to effectively manage workload and ensure data validity. Moreover, to address the limitations of using MRI and radiography, and to manage a large number of animals, the investigation was divided into three stages, as illustrated in 4/kg of human adipose derived mesenchymal stem cells on both knees one week after induction surgery. The other pig acted as the placebo group and received only the medium. However, in the first round, one of the pigs received the medium solution only in the right leg due to a technical error during anesthesia [4/kg of pig stem cells derived from umbilical cords of pigs on both knees one week after surgery. Another pig acted as the control group and received no treatment, while the remaining pig served as the placebo group, receiving 1 mL of medium only. In the third and final stage of the experiment, two pigs were selected. One pig received an average of 30 × 104/kg of pig umbilical mesenchymal stem cells on both knees one week after induction surgery, while the other pig received an average of 36 × 104/kg of adipose-derived mesenchymal stem cells on both knees one week after induction surgery. Through this experimental design, our objective was to evaluate the impact of human and pig stem cells on knee joint healing through cartilage regeneration, while also observing the effect of the negative control group.In the first stage of the experiment, two pigs were selected, with one serving as the treatment group, receiving 28 × 10esthesia . In the ® 100 (virbac) along with xylazine 10%(w/v)  was used as anesthesia for minimally invasive surgery. The dosage was 5–10 mg/kg. Zoletil® 100 was administered intravenously (IV). Isoflurane was used to maintain anesthesia in operation by the anesthesia machine. Atropine  pre anesthesia medicine was used with a dosage of 0.05 mg/kg administered subcutaneously. The antibiotic cephazolin  was used for infection control. The dosage was 25 mg/kg twice a day, which was administered intramuscularly. Carprofen was provided to pigs after surgery as a pain relief method for knee pain. The drug’s recommended dose was 2.2 mg/kg, which was administered intramuscularly once or twice a day, depending on the severity of the wound and pain condition.Zoletil® 35 W) after the procedure  was applied near surgical parts. Following the skin incision, an articular cartilage defect was formed in the lateral femoral condyle of both knees. An 8 × 5 mm sterilized biopsy punch  was used to create an incision. The wounds were sutured with 4-0 Vicryl and surgical staples  was administered intramuscularly. Animals were induced by full dosage of mixture of Zoletil 100 (0.04 mg/kg) with xylazine (0.003/kg). Animals were taken to mercy animal hospital  with special care for MRI and CT examinations on every 4th and 6th weeks of stem cell implantation. Baseline was taken as 0 week before stem cell therapy . MRI andAfter eight weeks of stem cell treatments, the animals were euthanized in accordance with the protocol established by the Institutional Animal Care and Use Committee (IACUC). The animals were first administered a full dosage of a mixture of Zoletil 100 (0.04 mg/kg) and Xylazine (0.003/kg) to induce unconsciousness. Then, the knee joints were collected, pictures were taken, and evaluated using ICRS scoring  Table 2Table 2. For three days, MCs from joint cartilages were preserved in 4% buffered paraformaldehyde. After two weeks of decalcification in 0.5 M ethylene diamine tetra-acetate (EDTA) solution at four degrees Celsius, the samples were desiccated, embedded in paraffin, sectioned, and stained with hematoxylin and eosin (H&E). An optical microscope  and a digital camera  were used to evaluate the histologic sections. Five independent evaluators independently analyzed the severity of articular cartilage sections and scored them using the International Cartilage Repair Society (ICRS) histology grading method  Table 3Table 3. ® ELISA kits  as per the manufacturer’s instructions. The ELISA kits for all five cytokines were purchased from R&D Systems and used as per the manufacturer’s instructions. After the samples were diluted as appropriate, cytokine levels were evaluated using a four-parameter logistic (4-PL) curve fit. The results were presented as mean standard error (SEM).For the cytokine concentrations, blood from each group were collected; blood samples were centrifuged at 1500 g for 10 min and serum was preserved at −80 °C until use. The levels of various cytokines  were measured using the ELISA (enzyme-linked immunosorbent assay) technique with QuantikineDescriptive statistics such as mean and standard errors (S.E.) were used to summarize the data. The ANOVA was used to determine if there were significant differences among treatment groups in terms of cytokine concentration, gross grading score, and visual histological findings score. The one-way ANOVA in IBM SPSS version 26 software was used for analysis. Multiple comparisons were performed to compare treatment means using the Duncan and Tukey post hoc tests at a statistical significance level of 5%. The graphs were created with Microsoft Excel 2022 and the most recent version of R software which is R package version 1.3-5 (Agricolae 10).This study used magnetic resonance imaging (MRI) and computerized tomography (CT) as imaging modalities to accurately assess and monitor alterations in the knee joint. Specifically, MRI and CT scans were used at the fourth and sixth weeks of the study to validate the expected localization of damage resulting from treatments. The identification of any extra cases of joint infections or injuries in addition to arthritis was also made possible by these imaging techniques. At weeks 0, 4 and 6, MRI and CT scanning were carried out . Week 0 was used as the baseline time for MRI and CT imaging observations in order to evaluate the defect’s initial condition prior to any intervention . The resMRI results have been categorized according to various conditions. Sagittal views were chosen to compare each group. The T2 condition is an excellent method for demonstrating the difference between the damaged and repaired parts. The results of the MRI and CT scans showed notable improvements in the treatment group treated human adipose derived mesenchymal stem cells, especially in terms of improved cartilage formation and wound healing . Figure Eight weeks after surgery, the animals were euthanized with overdose of zoletil and xyzaline and the gross appearances of the defects were taken and studied . The conHematoxylin and eosin staining (H&E) was used to demonstrate the partial histological changes of regenerated cartilage in sample slides from all experimental groups . The micp < 0.05) than the control group for most parameters measured eight weeks after surgery. The placebo group had a higher mean overall score at eight weeks than the control group for surface and cartilage mineralization; however the difference was not statistically significant. Treatment groups, both hADSC and pUCMSC, had higher mean scores in some parameters, such as cell population, cell distribution, and subchondral bone. The mean score for cell population of hADSC was 1.875 ± 0.256, which was followed by pUCMSC with 1.687 ± 0.198. The mean score for the subchondral bone parameter of hADSC was 2.187 ± 0.208, which was also followed by pUCMSC with a mean score of 2.062 ± 0.192. There was a high level of agreement among the valuators. The mean histology score is shown in The ICRS histological scoring demonstrated that hADSC had significantly higher scores  have garnered considerable attention as a potential source for cartilage regeneration in large animal models, including pigs ,32,33. IThe concern about immune rejection was a crucial consideration in the experiment as the xenograft model was carried out. Upon conducting physical observations on the animal subjects during the study, no instances of immune rejection or tumor formation were observed in the pig’s body during the study. Gross observations at eight weeks after surgery revealed that the stem cell treatment group, particularly hADSC, had almost completely healed defects, with smooth surfaces on the restored cartilage. This contrasts with the control group, which had large fissures and penetration cracks. These findings are also consistent with previous studies that have reported the potential of stem cells for promoting tissue repair ,23,28. BThe process by which stem cells contribute to tissue regeneration and wound healing is underpinned by two hypotheses, namely the differentiation theory and the paracrine theory ,41. WhilThis study used a low-dose, single intra articular injection of MSCs that had no adverse effects on the experimental animals. The findings suggested a degree of safety and efficacy for a limited time as this xenograft model study is supported by the literature in terms of safety ,47,48. HThe regenerative effect of human adipose MSCs on chondrocyte growth in a porcine model is associated with an immune modulation without immune rejection or tumor formation in this study. The study used a pig model to evaluate the effectiveness of mesenchymal stem cells for regenerating cartilage in the knee. According to the study’s findings, hADSCs can aid in cartilage regeneration by promoting anti-inflammatory cytokines while reducing pro-inflammatory cytokines. This study opens the door to cartilage regeneration, potentially improving treatment techniques for OA in both humans and pets. However, further studies are needed to confirm these findings and establish it as a therapeutic option.


For decades, forensic scientists have investigated changes in post mortem body composition, focusing on different physical, chemical, or biological aspects, to discover a reliable method for estimating PMI; nevertheless, all of these attempts remain unsuccessful considering the currently available methodical spectrum characterized by great inaccuracies and limitations. However, recent promising approaches focus on the post mortem decomposition of biomolecules. In particular, significant advances have been made in research on the post mortem degradation of proteins. In the present study, we investigated early post mortem changes (during the first 24 h) in the proteome profile of the pig skeletal muscle looking for new PMI specific biomarkers. By mass spectrometry (MS)-based proteomics, we were able to identify a total of nine potential PMI biomarkers, whose quantity changed constantly and progressively over time, directly or inversely proportional to the advancement of post mortem hours. Our preliminary study underlines the importance of the proteomic approach in the search for a reliable method for PMI determination and highlights the need to characterize a large number of reliable marker proteins useful in forensic practice for PMI estimation.Estimating the time since death ( Post mortem interval (PMI) estimation is undoubtedly the most important factor in forensic science and the accuracy of this determination has always been a real challenge. Knowing the time since death helps reveal the circumstances of death and thus, in criminal cases, provides decisive evidence in court for the resolution of a crime Post morts of RNA . In parts of RNA ,8. Theres of RNA ,8.post mortem changes in this tissue occur more slowly compared to internal organs and nervous tissue  in the proteome profile of pig skeletal muscle (three samples per time-group) looking for new PMI specific biomarkers. We identified and quantified a total of 657 proteins from Sus scrofa (domestic pig) in the considered post mortem interval. According to protein intensities, a Hierarchical clustering was performed , directly or inversely proportional to the advancement of post mortem hours. We identified five proteins  whose intensity quantitatively decreased with increasing post mortem hours and 4  which increased, for a total of nine identified potential markers (By mass spectrometry (MS)-based proteomics, we investigated early the erformed . Observierformed , the dif markers a.post mortem changes (during the first 24 h) in the proteome profile of the pig skeletal muscle, looking for new PMI specific biomarkers. By mass spectrometry (MS)-based proteomics, we were able to identify a total of nine potential PMI biomarkers, whose quantity changed constantly and progressively over time, directly or inversely proportional to the advancement of post mortem hours: five proteins  whose intensity quantitatively decreases with increasing post mortem hours and four  which increase.In forensic science, the temporal reconstruction of the events represents a key point for the correct interpretation of the crime scene as it allows for the revealing of the dynamics of the criminal event. The determination of PMI can be decisive in reconstructing homicide cases and represents a continuous challenge in forensic research. In recent years, research to calculate the time elapsed since the death of a victim has been oriented towards the search for markers which are specificand reliable, but primarily free from exogenous and/or environmental interference. These new markers include the bloodstains aging  and the eEF2—Eukaryotic translation elongation factor 2—is involved in the translocation of eukaryotic protein synthesis. In the active form it is bound to GTP whose hydrolysis allows for the release of energy which can be coupled to the translocation . GPS1—G post mortem proteolysis. The phenomenon of protein decomposition is very complex and influenced by various factors that act synergistically in determining the ways and times of cleavage of native proteins into more or less small fragments. Among these factors, they are of great importance differences in amino acid sequence, post-translational modification, all in turn influencing spatial structure, molecule function, and accounting for variability in protease cleavage sites [Most studies analysing protein degradation in the early stages of PMI have highlighted a pattern of protein degradation or decrease. This phenomenon, which begins immediately after death, can be traced back to those enzymatic (proteolytic enzymes) and non-enzymatic processes  which jointly act to degrade proteins into smaller fragments ,24. Thisge sites ,26.postmortem, we, as well as other authors, have found that certain proteins show an increase after death, often followed by a subsequent decrease. We have highlighted four proteins that behave like this: SERBP1, COX7B, SOD2, and MAOB. SERBP1—SERPINE1 mRNA binding protein 1—is a messenger RNA binding protein that has a primary role in the regulation of mRNA stability and is involved in post-transcriptional mechanisms [However, although most of the proteins were found to decrease chanisms . In genechanisms ,29,30. Cchanisms . SOD2—Suchanisms . Therefochanisms . MAO—Monchanisms . Monoamipost mortem increase in the level of some proteins is often defined as unknown, although there are several possible explanations for this phenomenon. Since mass spectrometry data are normalized on protein median, the apparent increase in levels of some proteins might simply reflect an increase in the relative abundance, and not the absolute abundance. Proteins less subjected to degradation will increase their relative abundance in post-mortem samples. Alternatively, in very early post mortem phases, it could result from continued protein synthesis, as evidenced also by Sanoudou and coworkers, who reported a high transcriptional and possibly also translational activity during the first hours post mortem in skeletal muscle [post mortem in two model organisms: mouse and zebrafish, highlighting that in addition to the already mentioned genes involved in the onset and development of cancer, several upregulated genes were implicated in pathways related to apoptosis, inflammation, and different types of stress, such as oxidative stress [The cause of the counterintuitive l muscle . Anothere stress .postmortem muscle, therefore skeletal muscle metabolism changes from aerobic to anaerobic [postmortem muscle is biochemically active and some metabolic pathways do not stop instantly, while others are even started. Clearly, in adverse conditions, cells activate a wide array of mechanisms to re-establish homeostasis and to repair stress-induced molecular damage [2+ ions. Ca2+ fluxes not only regulate the bioenergetic and anabolic metabolism but also impact on the activation of cell death pathways and the response of cells to a wide number of perturbations, including oxidative stress [post mortem conditions might activate some oxidation related protein synthesis, while deactivating other proteins and metabolic pathways. For example, the two-fold increase in the mitochondrial enzymes COX7B, SOD2, and MAOB leads us to assume that oxidative phenomena are triggered after death. Similarly, such post mortem conditions may also influence other proteins that do not tend to show continuous increase or decrease. In distinct cases, the transient increase in a marker could be due to the loss of inhibition during life. The inhibitory units of enzymes can dissociate when membrane potentials break down, as exemplified by calpain activation caused by post mortem Ca2+ increased levels.After death, oxygen is not delivered by the circulatory system to naerobic . Anyway,r damage . In partr damage . In addir damage . This oxr damage . Mitochor damage . Togethee stress ,42. ThesThis study has potential limitations. First of all, the results obtained with an animal model are not directly transferable to humans. The use of pigs as a prototype species represents the best choice for forensic studies, as the pig anatomy and physiology present a high resemblance to humans, but comparing two species will be subject to uncertainties. Furthermore, in our preliminary study we evaluated only one specific state (death by bleeding of organisms with high BMI in an environment with non-extreme and relatively constant temperatures), thus numerous other experiments are necessary to validate the obtained results and the applicability to real forensic casework.Sus scrofa domesticus), weighing about 120 kg , were used for this study. Animal samples were obtained from a commercial slaughterhouse. Muscle tissue was sampled from the belly of the musculus biceps femoris of the left hind limbs at pre-defined post mortem time intervals  during the maturation of the whole animal at a temperature between 12 and 18 °C. For sampling, an incision was made through the skin and the underlying fascia using a surgical sterile scalpel, and a piece of muscle tissue, with a size of approximately 2 × 2 × 2 cm (~2 g) was excised in a depth of 2 cm. To avoid artificial desiccation and contamination effects, the minimum distance between sampling sites (for each new time point) was 5 cm. The samples collected each time were sectioned to smaller pieces of approximately 100 mg, snap frozen in liquid nitrogen, and stored at −80 °C until further processing. Frozen tissues were homogenized manually, using a prechilled mortar and pestle, in ice-cold RIPA buffer containing a protease inhibitor cocktail . After centrifugation for 20 min at 14,000× g at 4 °C, supernatants were collected and stored at −20 °C until further use. Protein concentration was determined by spectrophotometry using the Bradford method .Three male (castrated) breeding pigs  unless otherwise specified.g for 15 min. Subsequently, two washes were performed with urea buffer . Cysteine alkylation was performed with 50 mM iodoacetamide (IAA in 8M urea buffer) for 20 min. Before the addition of the trypsin enzyme, two washes with urea buffer and two washes with 50 mM TEAB were performed. Then, 500 ng of trypsin were added to each sample for digestion at 37 °C overnight. The following day 140 µL of H2O were added and the samples were centrifuged at 14,000× g for 20 min to collect 180–200 µL of digest.FASP digestion—Supernatant 100 μL (50 µg) were dissolved in SDS 1%, 50 mM DTT, and 50 mM Tris HCl pH 8.0 and heated at 95 °C for 10 min. Protein samples were added to the filter unit  and centrifuged at 14,000× 3 of EmporeTM-3M SCX resin (Merck Millipore). The digested samples were acidified by adding 80% acetonitrile-0.5% formic acid (Solution W2). The StageTip was conditioned by adding 20% acetonitrile-0.5% formic acid  and 50 µL of W2. Peptides were loaded by slowly letting the fluid pass through one plug using a benchtop centrifuge. After 2 washes with 50 µL of Solution W2 and 50 µL of Solution W1, respectively, peptides were eluted by adding 10 µL of 500 mM ammonium acetate-20% acetonitrile.Peptides purification—Peptides (5 µg) were purified by strong cation exchange (SCX) StageTips method, aiming at removing eventual detergent residues. The stationary phase was 1 mmm/z. The maximum injection time was set to 50 ms for full MS scans and to 120 ms for MS/MS scans.LC-MSMS analysis—LFQ (label free quantification) analysis was performed by an LC-MS/MS system consisting of an Easy nLC-1000 chromatographic instrument coupled to a Q-Exactive-Orbitrap mass spectrometer . All the LC-MS/MS analyses were carried out at 230μL/min flowrate and peptides were eluted by using two mobile phases: A (0.1% FA in 2% ACN) and B . LC-MS/MS analysis was performed in data-dependent acquisition (DDA). The full scan m/z range was 350–1800, followed by MS/MS scans on the 12 most intense precursor ions. DDA analysis was performed with resolution for full MS scan of 70,000 and of 35,000 for MS/MS scan; the isolation window was 1.6 Sus Scrofa proteome database .For LF samples the following settings were used: fixed modifications: carbamidomethyl (C); variable modification: oxidized methionine (M) and acetyl (N-terminus). Unique peptides were used for protein identification. Forthe statistical analysis of MaxQuant output, the Perseus software (1.6.1.3 version) was used as follows: the LFQ intensity of proteins from the MaxQuant analysis were imported and contaminants, reverse identification, and proteins only identified by site were excluded from further data analysis. Data were transformed in logarithmic scale (log2). Proteins quantified in less than two replicates belonging to at least one group were discarded. The remaining missing LFQ values were imputed from a normal distribution . Finally, for the whole data sets, two-sample t-test was used to assess statistical significance of protein abundances .Raw MS data (available in post mortem is still quite limited. Because of complex post mortem conditions and the influence of several factor, PMI estimation based on the behaviour of one or a few proteins is not pragmatic. In this study, we exploited a mass spectrometry-based proteomics approach to profile post mortem proteome alterations in skeletal muscle tissue and to characterize additional marker proteins for future use in PMI determination. In conclusion, despite the previously indicated limitations and the preliminary nature of our study, in this work we identified a total of nine potential markers, some of which had a decreasing trend and others an increasing one. The overall intersection of the data obtained from the variations in several markers, both in terms of increase and decrease, could be fundamental to estimate the PMI with increasingly accuracy and precision. This proteomic approach is highly functional for the characterization of reliable marker proteins useful in forensic practice. To obtain an improvement in the accuracy and overall precision in the PMI estimation it is necessary to characterize several markers even on different species, prolonged time intervals, or variable environmental conditions. In particular, investigations of the human post mortem proteome could contribute crucially to the characterization of important additional biomarkers.Protein-based analysis for time since death estimation has emerged as a promising tool in recent years, although the spectrum of target proteins that are known to undergo predictable changes in early and mid-


This retrospective study using the propensity score (PS) matching method aimed to explore whether the presence of oocyte degeneration in conventional IVF cycles would affect the sibling embryo development potential and clinical outcomes.Oocyte degeneration was mostly described in intracytoplasmic sperm injection (ICSI) cycles; there is no report showing the relationship between oocyte degeneration and clinical outcomes in conventional Patients with at least one oocyte degenerated after short-term insemination and stripping were defined as the degeneration (DEG) group, while patients with no oocyte degenerated were defined as the non-degeneration (NONDEG) group. The PS matching method was used to control for potential confounding factors, and a multivariate logistic regression analysis was made to evaluate whether the presence of oocyte degeneration would affect the cumulative live birth rate (CLBR).After PS matching, basic characteristics were similar between the two groups, oocyte yield was significantly higher in the DEG group than the NON-DEG group (P < 0.05), mature oocyte number, 2 pronuclear (2PN) embryo number, 2PN embryo clearage rate, “slow” embryo number, “accelerated” embryo number, rate of cycles with total day 3 embryo extended culture, number of frozen embryo transfer (FET) cycles, transferred embryo stage, transferred embryo number, and live birth rate in fresh embryo transfer cycles were all similar between the two groups (P > 0.05), but the 2PN fertilization rate, available embryo number, high-quality embryo number, “normal” embryo number, frozen embryo number, blastocyst formation rate, and no available embryo cycle rate were all significantly lower in the DEG group than the NON-DEG group (P < 0.05). The cumulative live birth rate was also significantly lower in the DEG group than in the NON-DEG group . Multivariate logistic regression analysis further demonstrated that the presence of oocyte degeneration in conventional IVF cycles adversely affects the CLBR both before  and after  PS matching.Our findings together revealed that the presence of oocyte degeneration in a cohort of oocytes may adversely affect subsequent embryo development potential and clinical outcomes in conventional IVF cycles. Informed consent was not necessary because this retrospective research was based on non-identifiable records.This retrospective study was performed at the reproductive medicine center of The Affiliated Chenggong Hospital of Xiamen University. Patients who underwent conventional IVF treatment from 2013 to 2019 were enrolled and retrospectively analyzed. The exclusion criteria were as follows: (a) patients proposed to take IVF treatment but eventually underwent early rescue ICSI treatment because less than 50% of mature oocytes excluded their second poly body. (b) Patients got no live birth but still had frozen embryos 2 years later after oocyte collection in one OPU cycle. A total of 14,665 patients who took 16,823 conventional IVF cycles were included, of which 2,776 cycles presented at least one oocyte degenerated after short-term insemination and denuding on the OPU day, and 12,921 cycles took fresh embryo transfer. Cycles with at least one oocyte degenerated were defined as the degeneration group (DEG Group), and cycles with no oocytes degenerated were defined as the non-degeneration group (NON DEG Group).2 level every 1–3 days. Oocyte retrieval was performed using transvaginal ultrasound, and a 17 G needle  was used for oocyte pick-up.Most patients in our center used a Gonadotropin-releasing hormone (GnRH) agonist or an antagonist protocol as we previously described , 10; som5 progressively motile spermatozoa in fertilization culture medium  for approximately 5 h, and then oocytes were denuded for the observation of the second poly body. Patients with more than 50% mature oocytes excluding the second poly body underwent conventional IVF treatment, while early rescue ICSI was performed on patients with less than 50% mature oocytes excluding the second poly body 6 h after insemination. Early rescue ICSI patients were excluded in this study. Considering oocyte degeneration definition in ICSI cycles  in traditional incubators  at 37°C, 6% COcriteria , and we criteria . BlastocA vitrification protocol was used for embryo cryopreservation, which employed 15% dimethyl sulfoxide, 15% ethylene glycol, and 0.6 M sucrose as cryoprotectants. For embryo thawing, embryos were directly immersed into a thawing solution (TS) containing 1 M sucrose at 37°C for 1 min. Then, they were sequentially incubated in each of the following solutions for 3 min: 0.5 M sucrose, 0.25 M sucrose, and sucrose-free TS, and embryos were placed in blastocyst culture medium  and cultured normally.Embryo transfer was performed using a COOK catheter  under trans-abdominal ultrasound guidance.The cumulative live birth rate (CLBR) was calculated in this study, and we used a short-term calculation method as previously described . The CLB2 level on the hCG day, and survival oocyte number (retrieved oocyte number minus degenerated oocyte number). Considering degenerated oocytes decreased the survival oocyte number and may affect cumulative live birth, we take the survival oocyte number as a variable in the PS matching method. A one-to-one nearest neighbor matching method without replacement was performed to match data between the DEG group and the NON DEG group with a caliper width equal to 0.2. PS matching was performed by using the MatchIt package in R software , gonadotropin total dose, the length of stimulation, gonadotropin starting dose, Esoftware . The cobsoftware  was usedsoftware .Data were presented as mean (SD) and median (first quartile and third quartile) for continuous variables and n (percentage) for categorical variables. Continuous variables were analyzed using the Wilcoxon test, and categorical variables were analyzed using the chi-square test or Fisher’s exact test; P < 0.05 was considered to be significant. All analyses were performed by using R statistic software 4.12 .Multivariate logistic regression analysis was also performed to evaluate the association between oocyte degeneration presence and the probability of cumulative live birth, with adjustments made for important covariates and potential confounding factors.We used generalized additive models (GAMs) to verify whether there is a dose-dependent association between degeneration and CLBR . In GAMsIn this study, 16,823 IVF cycles were enrolled and analyzed, 3,748 oocytes in 2,776 cycles were found degenerated after fertilization, the oocyte degeneration rate is 2.48% , and the degeneration cycle rate is 16.50% .2 level on the hCG day, and survival oocyte number (D > 0.1). After matching (right panel), all the baseline characteristics became very comparable between the two groups (D < 0.1). Distributions of the PSs before and after PS matching are shown in After PS matching, 2,776 cycles in the NON DEG group were matched by their counterparts in the DEG group. Basic characteristics before and after PS matching are shown in P < 0.05), mature oocyte number, fertilization oocyte number, 2PN embryo number, 2PN embryo clearage rate, “slow” embryo number, “accelerated” embryo number, the rate of cycles with total day 3 extended embryo culture, the number of FET cycles, transferred embryo stage, transferred embryo number, and live birth rate in fresh cycles were all similar between the two groups (P > 0.05), but the 2PN fertilization rate, both on the basis of oocyte yield (2PN number/oocyte yield *100%) as shown in P < 0.05). The available embryo number, high-quality embryo number, “normal” embryo number with seven to nine cells on day 3, frozen embryo number, blastocyst formation rate, and no available embryo cycle rate were all significantly lower in the DEG group than the NON DEG group (P < 0.05). These findings revealed that the presence of oocyte degeneration in a cohort of oocytes may affect subsequent embryo development potential. The cumulative live birth rate was also significantly lower in the DEG group than the NON DEG group  after PS matching.We also conducted a multivariate logistic regression analysis, with adjustments made for important covariates and potential confounding factors; logistic regression analysis results in To our best knowledge, this is the first study to investigate oocyte degeneration in conventional IVF cycles on the OPU day. Despite the surviving number of oocytes and the patient’s characteristics being comparable following PS matching, our results showed that the cumulative live birth rate of the completed cycles was significantly decreased in the DEG group than that in the non-DEG group, suggesting an overall decrease in the oocyte quality. It was also supported by the findings that the numbers of available embryos, high-quality embryos, and “normal” embryos with seven to nine cells on day 3 were all significantly lower in the DEG group than in the NON-DEG group. For patients who had all their embryos extended culture, the blastocyst formation rate was also decreased with the presence of oocyte degeneration. Taken together, these results revealed that the presence of oocyte degeneration in a cohort of oocytes in conventional IVF cycles may be an unfavorable predictor for subsequent embryo development potential and clinical outcomes.In this study, we found that the percentage of conventional IVF cycles with oocyte degeneration on the OPU day is 16.50%, which is similar to previously reported at the time of OPU in both conventional IVF cycles and ICSI cycles . On the In ICSI cycles with oocyte degeneration, several studies reported that oocyte degeneration was not an indicator of the live birth rate , 18, andOur study conflicted with the work of Hu et al., which suggested that the cumulative live birth rate in young women was not affected by the presence of oocyte degeneration .The contIn addition to the insemination protocol and male infertility, the degree of ovarian response might also affect the evaluation of the association between oocyte degeneration and cycle outcomes. Pride et al.  reportedAtzmon et al.  reported2 level was demonstrated to be very important during oocyte development and maturation (2 on the hCG day may be negatively associated with the degeneration rate in GnRH agonist protocols, while Palermo et al. (2 level on the hCG day. Factors like the ovarian stimulation protocol and high levels of E2 are known to affect the physiological status of women and thus affect IVF outcomes (As we know, oocyte quality predominantly determines embryo quality –26, and turation ; Rosen eturation  reportedo et al.  reportedoutcomes –36. HoweWhile ICSI is absent in the conventional IVF cycles, oocyte degeneration may also be affected by technical factors, such as OPU needles and oocyte denudation pipettes. Pride et al.  deduced This study was limited by its retrospectively observational design, and the results could be screwed by unrecorded or unmeasured confounders. Although PS matching was used to minimize the confounding bias, the sample size decreased after PS matching, and the loss of unmatched samples may include biased ones; thus, we also analyzed the pre-matched data by using multivariable logistic regression analysis and got the same reassuring conclusion.In most clinics during conventional IVF procedures, cumulus–oocyte complexes are usually incubated with spermatozoa overnight and the real oocyte structure is unknown on the oocyte pick-up day , 38. TheIn conclusion, we first reported oocyte degeneration in conventional IVF cycles on the OPU day in this study. Our results showed that the oocyte degeneration rate and degeneration cycle rate on the OPU day in conventional IVF cycles were all much lower than in ICSI cycles , 8. The The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethical Committee of Medical College Xiamen University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.LL, JLC, and JR contribute to conception and design. JHC, CY, KC, and XY contribute to the acquisition of data. LL, XJ, and ZL contributed to the analysis and interpretation of data. All authors contributed to drafting the article or revising it critically for important intellectual content. All authors contributed to the article and approved the submitted version.


Restricted motion during touch screen device use may contribute to wrist overuse injuries. Wrist radioulnar deviation and extension while using touch screen devices and digital or manual counterparts in male and female medical professional dominant and non-dominant hands were quantified to test the hypothesis that mobile touch screen device use reduces wrist motion.An active motion detection system was used to record wrist motion of 12 participants while: tablet swiping and turning book pages; raising a cell and traditional phone to the ear; texting and typing; and entering numbers on a cell phone and manual calculator. Medial and lateral wrist surface range of motion (ROM) and minimum and maximum wrist radial-ulnar deviation and flexion-extension were quantified.Device, sex and handedness effects were determined (P<0.05). Maximum medial radial deviation and ROM were greater using a cell versus traditional phone. Maximum medial radial deviation was higher in the nondominant wrist during backward tablet swiping and while backward page turning versus tablet swiping. Maximum and minimum medial extension angles and ROM were greater while typing versus texting. Female nondominant hand maximum lateral extension and ROM were greater for typing versus texting and maximum medial extension and lateral extension ROM greater during manual versus cell phone calculator use with handedness combined. Maximum lateral extension and ROM were greater in females versus males using manual calculators.Sex and handedness should instruct touch screen, digital and manual device design and use for optimal performance and injury prevention. Complex wrist anatomy and nearly continuous motion during daily activities contribute to high propensity for overuse injuries . RepetitWrist angles and ROM are typically measured in flexion-extension and radial-ulnar deviation as two- or three-dimensional angles, and dynamic wrist kinematic measures requires real-time data collection technology like optical motion capture systems . The wriThe functional range of motion for the human wrist is determined during activities of daily living but do not usually include mobile or digital devices . Device The study was approved by the institutional review board (Protocol #9078) and study subjects gave informed written consent to participate. Equal numbers of male or female medical school personnel with left or right dominant hands completed a series of activities in identical order. Inclusion criteria included: (1) 20 to 40 years old; (2) single dominant hand (no ambidexterity) according to the Edinburgh inventory ; (3) no Devices included in this study  included® adhered to the skin with wig adhesive and to the markers and drive boxes with cyanoacrylate glue. The medial surface carpal angle vertex was the intersection of vectors between markers on the 2nd metacarpal bone base and trapezium and markers on the radial styloid and radius midpoint. The lateral surface carpal angle vertex was formed by the intersection of vectors formed by markers on the 5th metacarpal bone head and hamate and markers on the ulna styloid and ulnar midpoint  of a 3D active motion detection system (Charnwood Dynamics Ltd) were affixed to the skin over anatomical landmarks on the medial and lateral surfaces of the forearm, wrist, and hand: 5th metacarpal head, hamate, ulnar styloid, ulna midpoint, 2nd metacarpal head, trapezium, radial styloid, and radius midpoint. The markers and two marker drive boxes were attached to the skin with pieces of VELCROmidpoint .Participants were seated in an office chair at a desk that was adjusted in height so the elbow rested on the table while flexed at about 90° with the shoulder relaxed. Each performed 4 activities with the dominant hand first. Immediately prior to each activity, subjects practiced with the designated hand three times. A tone triggered participants to start three repetitions of an activity within 15 seconds when another tone sounded. During activities, participants rested their forearms on the desk surface, and between repetitions, rested their hands and forearms on the desk surface in a prone  position . ActivitData was collected at 200 Hz and included when marker visibility was 80–100% for a repetition. Angles were selected for each activity that were consistently measurable and corresponded to the predominant motion. Radial deviation was quantified for raising a cell phone or receiver to the ear and swiping or turning pages backward, ulnar deviation for swiping or turning book pages forward, and extension for texting, typing, and entering numbers on a cell phone and manual calculator. Two-dimensional, minimum and maximum extension (y-z plane) and radial and ulnar deviation (x-y plane) angles of the lateral and medial joint surfaces were recorded by the system software  and exported to spreadsheet software . The software setup included use of individual marker identities to create the medial and lateral free vectors, ectively . The two® Pro v. 14 and significance considered at P ≤ 0.05.Results are presented as least squares mean (LSM) ± SEM. Normal data distribution was confirmed with the Shapiro-Wilk test. A mixed ANOVA model with fixed effects of sex, handedness, activity, and their interactions, and random effect of participant was used to evaluate differences between sexes, touch screen and digital or manual devices, and dominant versus nondominant hands for each wrist surface. Fixed effects were evaluated for each activity with Fisher’s least significant difference post-hoc comparisons. Results were combined for fixed effects that were not significant for an activity. All statistical analyses were performed with JMPAll results are provided as LSM ± SEM Tables  and 2. TP = 0.04; and 7.4 ± 1.0 versus 4.6 ± 1.12, P = 0.01) with sex and handedness combined phone (P = 0.04), and the angle was greater in the nondominant versus dominant wrist with sexes combined  and the minimum medial extension angle was smaller for texting , the maximum lateral extension angle was greater in females versus males while using a manual calculator , and the lateral carpal extension ROM was greater in females versus males while using a manual calculator  and in females while using a manual versus cell phone calculator (21.0 ± 3.7 versus 7.8 ± 3.7, P = 0.01; The maximum medial radial deviation angle and medial radial deviation ROM were greater using a cell versus a traditional phone receiver (13.5 ± 1.6 versus 7.7 ± 2.3, ed phone . The maxThe hypothesis, mobile touch screen device use reduces wrist motion, was rejected because it was not true in all tested devices. Specifically, medial radial deviation and ROM were higher using a cell versus traditional phone. However, swiping on a tablet, texting, and using a cell phone calculator did appear to reduce wrist motion relative to manual or digital counterparts. Differences in wrist motion for specific devices were also evident between sexes and dominant versus nondominant hands, and many were distinct between medial or lateral wrist surfaces. The results indicate that wrist motion using touch screen and manual or key activated digital devices varies with joint surface and are affected by sex and handedness, important considerations for device design and use recommendations to prevent overuse injury.Many detectable differences in wrist motion among devices in this study were with sex and handedness combined, presumably because their effects are inseparable for many activities. The higher medial radial deviation associated with cell phone use exemplifies this point. Cell phones tend to be wider than standard phone receivers, and the distance between the hand and ear with a cell phone is shorter than with a receiver. Wrist radioulnar deviation during merchandise bagging was greater when grasping 10 cm versus 5 cm diameter objects . In thisThe maximum medial radial deviation for page turning versus swiping and maximum medial extension and ROM and minimum medial extension for typing versus texting were sufficiently distinct between devices, but not hand or sex, to be detected. However, motion was lower for touch screen devices. While the initial direction, radial or ulnar deviation, for backward page turning or swiping was different depending on the hand, left or right, in use, only medial radial deviation was significantly higher for page turning. The process of semi-grasping, elevating, and releasing a book page requires more complex wrist motion than swiping on a tablet, and swiping requires sustained contact in a more constrained space . GreaterThere is no universally accepted model of carpal bone motion, but current understanding is that the distal row, hamate, capitate, trapezoid, and trapezium, moves more uniformly than the proximal row, triquetrum, lunate, and scaphoid , 37. VarThe angles and ROM measured in this study are not all extremes of wrist motion , 41. ConDifferences in wrist deviation and flexion-extension vary between sexes and hands . Better Results should be limited to the comparisons here within study limitations. Markers were on bony landmarks where subcutaneous tissue was minimal, so skin motion was minimized but not obviated. The markers and marker boxes attached to the forearm could have affected normal wrist motion of participants, and the effects might have varied among individuals. Task order was not randomized, though 10–15 minutes between tasks should minimize carryover effects. Due to busy medical trainee schedules, it was not possible to repeat tasks on different days to test repeatability. The small participant population, medical trainees in an age range with high wrist ROM, though consistent with comparable studies, may limit generalizability of study findings , 47, 51.New information from this study that examined medial and lateral wrist motion during use of touch screen devices and digital and manual counterparts confirms distinct wrist motion between dominant and non-dominant hands that varies between male and female users. Maximum and minimum joint angles provide added information that may expand understanding of musculoskeletal disorders associated with the devices evaluated. Methods and results specific to wrist surface and maximum and minimum motion may also provide a platform for future studies. Taken together, results confirm that sex and handedness should guide recommendations for digital and manual device design and use to optimize performance and reduce injury.


Loin pain hematuria syndrome (LPHS) is a rare clinical syndrome with a reported prevalence of 1 in 10,000. The syndrome is characterized by severe pain localized to the kidney in the absence of identifiable urinary tract disease. Because of an inadequate understanding of the pathophysiology of the disease, the goal of management has been limited to symptomatic pain management. Through detailed phenotype and genotype assessment we sought to identify possible underlying etiologies.COL4A3, COL4A4, and COL4A5) gene sequencing in 14 patients with loin pain hematuria recruited from a single center.We completed a chart review, ultrasound imaging, kidney biopsy, and type IV collagen  was normal in 11 patients and thickened in 1 patient. Staining for IgA kappa was present in 1 patient. C3 deposition without any inflammation was present in 7 patients. Arteriolar hyalinosis was present in 4 patients and endothelial cell injury was present in 6 patients. No pathogenic Conventional histopathology and genetic testing for type IV collagen variants failed to identify the cause of hematuria in 14 patients with LPHS.  Since its first description by Little and colleagues in 1967, the etiology of LPHS remains poorly understood.COL4A3, COL4A4, and COL4A5) have increasingly been recognized as common causes of glomerular hematuria. Hemizygous severe pathogenic variants in COL4A5 lead to classical Alport syndrome in boys and young men with hematuria, proteinuria, and rapid decline in estimated glomerular filtration rate as well as extrarenal manifestations of ocular and hearing abnormalities. Nevertheless, the population prevalence of heterozygous type IV collagen variants was about 1 in 1000 in the UK biobank, which is 5 to 16 times more frequent than historic prevalence estimates of Alport syndrome.For glomerular hematuria to occur, red blood cells need to pass a 3-layered barrier consisting of glomerular endothelial cells, GBM, and podocytes.et al..,,,The mechanism of pain in LPHS is also unclear. There is a consensus that the hematuria is glomerular in origin but it remains uncertain if the pain is interrelated with the hematuria. In 1996, Hebert COL4A3, COL4A4, and COL4A5.Because there are gaps in our understanding, we sought to assess the histopathological features on kidney biopsy in 14 patients with loin pain hematuria, and specifically, to evaluate the correlation of GBM alterations by electron microscopy with hematuria. Further, in keeping with the recent advances in our understanding of type IV collagen’s role in hematuria, we performed targeted sequencing of Eighteen consecutive patients referred to nephrology clinic (run by the corresponding author) were approached by a study coordinator and 14 agreed to participate in the study . BecauseDemographic data, including sex, age, and self-reported ethnicity, was gathered. Phenotype information including age of onset of symptoms, comorbidities , weight, height, smoking status, and current medications was reported by patients. Morphine milligram (mg) equivalent per day was determined by using an equivalency factor to calculate a dose of morphine that is equivalent to the used opioid. Family history of LPHS, kidney stones, chronic kidney disease or end-stage kidney disease, or chronic pain was collected.After enrollment, serum creatinine and electrolytes; complete blood count; and urine dip, microscopy, and albumin-to-creatinine ratio were measured. All patients underwent a cystoscopy, ultrasound assessment of the kidneys and urinary tract, triphasic computed tomography of the abdomen and pelvis with delayed images, and split function mercaptoacetyltriglycine scan to assess the relative function of the kidneys. All patients had a negative urological assessment for causes of pain and hematuria .Patients underwent kidney biopsies from December 2020 to May 2021 at the Regina General Hospital, Saskatchewan, Canada. Kidney biopsies were performed by an interventional radiologist under realtime ultrasound guidance. Three cores were taken with a spring-loaded biopsy gun using an 18-gauge needle . All biopsies were read by a single kidney pathologist (PD) at the Department of Pathology and Laboratory Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. The samples obtained were divided into 3 portions for light microscopy, immunofluorescence, and electron microscopy (EM). The sample for light microscopy was fixed in formalin and embedded in a paraffin block. Sections of 1 to 3 mm thickness were cut and stained with hematoxylin and eosin, periodic acid–Schiff, Masson trichrome, and periodic acid silver methenamine special stains. The prepared slides were assessed using Nikon Eclipse Ci  microscope, using magnifications from 40 to 600 times. Each case was assessed and scored for global and segmental glomerulosclerosis, tubular injury, interstitial fibrosis and tubular atrophy, arteriosclerosis, arterial intimal fibrosis, and presence of red blood cells or degenerated red cell casts in tubules.Direct immunofluorescence was performed by adding fluorescein-conjugated antibodies against immunoglobulin heavy chains , light chains (kappa and lambda), complement components , and albumin using Benchmark ULTR system from Roche Diagnostics following the manufacturer’s instructions. Samples were then examined under blue laser light using an immunofluorescent microscope.et al.Ultrathin sections were stained with uranyl acetate and lead citrate before examination under the transmission electron microscope . GBM thickness was measured digitally using an EM image analysis system after calibration. Measurements were obtained in properly oriented open peripheral glomerular capillaries, with a minimum of 3 measurements evenly distributed per loop. GBM measurements were obtained in a minimum of 10 glomerular capillary loops of at least 2 viable glomeruli when possible. Mean and range of GBM thickness were then calculated and recorded for each sample. For standardization, mean and range of GBM thickness were reported for each sample, as previously reported.COL4A3, COL4A4, and COL4A5 was captured using hybridization probes. Captured DNA was pair end sequenced (150 × 2) on NovaSeq6000 using Illumina’s reversible dye terminator technology. The Clinical Laboratory Improvement Act certified laboratory used the following quality control metrics: >98% of targeted bases covered at >20× and mean coverage of target bases >100×. Copy number evaluation defined as single exon or larger deletions or duplications (Del/Dups) were detected from the sequencing data by the Clinical Laboratory Improvement Act laboratory using their proprietary bioinformatics pipeline. All sequencing results were reviewed and interpreted by clinical molecular geneticists. All sequencing results were reviewed and interpreted by clinical molecular geneticists. Sequence variants were categorized as “pathogenic”, “likely pathogenic”, “benign”, “likely benign”, and “variant of uncertain significance” as per American College of Medical Genetics Guidelines.Genetic testing was performed at Clinical Laboratory Improvement Act certified clinical laboratory approved by Saskatchewan Health Authority. DNA was extracted from leukocytes obtained from whole blood specimens. Sequencing included coding regions and 10 bases of exon flanking region. DNA corresponding to Descriptive statistics were used to report baseline characteristics and histology findings. Results were expressed as count (%) for categorical variables and median (interquartile range) for continuous variables.Among 18 patients who were approached, 14 agreed to participate and their baseline characteristics are in 2). We were unable to assess GBM thickness on EM for 1 patient because of inadequate sample. Red blood cells or red cell casts were present in the tubules or glomerular space of 10 patients (71%)  c.Table 2COL4A3, COL4A4, and COL4A5 genes in all 14 participants, there were no identified “pathogenic” or “likely pathogenic” variants. There was no evidence of copy number variations identifiable in the sequencing data.After successful sequencing of the COL4A3, COL4A4, or COL4A5 variants in this cohort of patients with loin pain hematuria. Based on these results, conventional histopathology and genetic testing for type IV collagen variants failed to identify the cause of hematuria in 14 patients with LPHS.We present kidney biopsy results and type IV collagen sequencing in 14 unrelated patients with LPHS. Eleven of 14 had a normal appearing GBM, whereas 1 of 14 had a thick GBM and 1 of 14 had evidence of IgA deposition. Red blood cells (10/14) or red cell casts (7/14) were present in multiple tubules in the majority of patients consistent with a glomerular source of bleeding. We did not identify any pathogenic et al.If a biopsy is performed in a patient with isolated hematuria, examination of the GBM using EM is usually viewed as the most important component. A case series of 7 patients in 1996 reported an absence of GBM abnormalities but presence of red cells in multiple cross-sections of renal tubules, indicating that the hematuria was glomerular in origin.COL4A5 variants,COL4A3 or COL4A4,COL4A3 or COL4A4 variants, or heterozygous COL4A5 in women can present with a range of histological and phenotype features variably, including hematuria, proteinuria, focal segmental glomerulosclerosis, and chronic kidney disease.COL4A3, COL4A4, and COL4A5 genes leading to a reclassification of Alport syndrome and thin basement membrane nephropathy as type IV collagen nephropathies.Increasing access to genetic testing has improved our understanding of the spectrum of phenotypes associated with type IV collagen nephropathy and a recognition that thin basement membrane disease and Alport syndrome share a common molecular basis.Deposition of C3, presence of arterial sclerosis, and endothelial cell injury were present in patients in this LPHS cohort but similar abnormalities have been reported in studies of healthy kidney donors. Of 102 transplant donors who underwent a kidney biopsy before transplant, 74.5% showed nonspecific IgM or C3 deposits, intimal fibrosis of small arteries (44%), interstitial fibrosis (8%), and arteriolar hyalinosis (29%).,et al.It remains possible that yet unidentified defects in the endothelium and GBM lead to the leakage of red cells from the vasculature into the urinary filtrate. Red cell transit through the GBM has been associated with a transient 2.25 μm wide gaps in the endothelium and underlying basement membrane.LPHS is likely not a distinct clinical entity but a common end point for a diverse group of underlying disease processes that manifest clinically with loin pain and hematuria. The histological changes identified in our study offer no consistent explanation for the genesis of the hematuria or pain or further basis for patient subclassification. Pathogenic type IV collagen variants are unlikely to explain a significant proportion of patients with LPHS but future genomic studies investigating additional genes that code for the GBM, proteins important for glomerular endothelial cell function, or the remainder of the exome and genome may provide additional clues. Given its rarity, genetic and genomic efforts will focus on families with multiple affected individuals.N = 420) that code for transduction, conduction, synaptic transduction, and modulation.Incapacitating, debilitating, opioid requiring pain remains a prominent feature of LPHS and its pathophysiology remains a mystery. The transmission of pain from the viscera to the brain involves a pathway that is controlled by an intricate series of genes (Limitations of the current study include the small sample size conducted in a single center, which limits generalizability. However, LPHS is a rare condition and as a regional referral center, we have attempted to capture as many patients as possible. All the patients were female and majority were of European heritage. Additional studies are on-going and collaboration is welcome.In conclusion, LPHS remains a disabling chronic condition primarily impacting women of reproductive age whose pathophysiology remains unknown. Kidney biopsy histology and sequencing of the type VI collagen genes in our cohort of 14 patients did not provide additional clues to the mechanism of hematuria or pain in patients with LPHS.This research was supported partially with a generous grant by The Hospitals of Regina Foundation. BP reports speaker and advisory fees from Bayer, Otsuka, Glaxo Smith Kline, Astra Zeneca, and Medtronic. MBL reports speaker and advisory fees from Otsuka, Bayer, Reata, and Sanofi. All authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.


CXCL10 was identified as the shared hub gene by the interaction network analysis of the corresponding WGCNA module gene to each disease, and CXCL10 was further identified as the shared specific gene by two machine learning algorithms. Additionally, we identified 3 RA-associated characteristic intestinal flora  and built a network of interactions between the microbiomes, genes, and pathways. Finally, it was discovered that the gene CXCL10 shared between IBD and RA was associated with the three gut microbiomes mentioned above. This study demonstrates the relationship between RA and IBD and provides a reference for research into the role of the gut microbiome in RA.This study aimed to identify shared specific genes associated with rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) through bioinformatic analysis and to examine the role of the gut microbiome in RA. The data were extracted from the 3 RA and 1 IBD gene expression datasets and 1 RA gut microbiome metagenomic dataset. Weighted correlation network analysis (WGCNA) and machine learnings was performed to identify candidate genes associated with RA and IBD. Differential analysis and two different machine learning algorithms were used to investigate RA’s gut microbiome characteristics. Subsequently, the shared specific genes related to the gut microbiome in RA were identified, and an interaction network was constructed utilizing the gutMGene, STITCH, and STRING databases. We identified 15 candidates shared genes through a joint analysis of the WGCNA for RA and IBD. The candidate gene  A small-sample study on patients with RA reported that most patients had subclinical intestinal inflammation4. Intestinal inflammation can be caused by and sustained through gut dysbiosis6. Inflammatory bowel disease (IBD), which encompasses Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic, recurrent inflammatory illness of the gut with immune system disturbance7. Despite having different target organs, IBD and autoimmune rheumatic illnesses share a genetic foundation10.Rheumatoid arthritis (RA) is an autoimmune inflammatory condition that primarily affects the joints. Individuals at risk for and those with RA experience gut dysbiosis11. Patients with RA have aberrant intestinal barrier permeability, which is consistent with the intestinal alterations observed in patients with IBD12. The IL-23/IL-17 inflammatory axis is activated during the development of both RA and IBD13. The expression of ENA78/CXCL5 is increased in tissues that are inflamed during RA and IBD15. Additionally, patients with RA and IBD have higher IL-6 levels18. These findings highlight the role of the gastrointestinal system in the development of RA and suggest a shared pathogenic mechanism between IBD and RA. However, the role of the gut microbiome in the pathogenesis of RA and the genetic interactions and molecular mechanisms underlying the relationship between RA and IBD remain unclear.According to a population-based study from South Korea, RA is strongly associated with IBD19. Isabelle Ayoub et al. used machine learning to assess the treatment response for lupus nephritis using standard clinical data with novel biomarkers20.Machine learning technologies have been widely applied in the study of inflammatory diseases in recent years. Using machine learning and deep learning, Maria Giovanna Danieli et al. investigated how intravenous and subcutaneous immunoglobulin treatment affects patients with idiopathic inflammatory myopathiesIn this study, bioinformatic tools were used to identify the common specific genes and processes between RA and IBD and examine the relationship between the gut microbiome in RA and the shared specific genes. We comprehensively analyzed four gene expression datasets from the Gene Expression Omnibus (GEO) database  and an RA-related metagenomic sequencing dataset, PRJEB6997, from the GMrepo database. Weighted correlation network analysis (WGCNA) was performed to identify candidate genes associated with RA and IBD. Gene set enrichment analysis (GSEA) was performed to assess changes at the pathway level. The shared specific genes between RA and IBD were screened using two types of machine learning algorithms and receiver operating characteristic (ROC) curves. The characteristics of the gut microbiome in RA were examined using differential analysis, two types of machine learning algorithms, and ROC curves. Subsequently, the shared specific genes related to the gut microbiome in RA were identified, and an interaction network of these genes and those related to shared GSEA pathways were constructed using the gutMGene, STITCH, and STRING databases. The Spearman correlation analysis was used to determine the connection between these genes and immune cells. To the best of our knowledge, this study is the first to report the common genes associated with both RA and IBD and their relationship with the gut microbiome in RA using a systematic bioinformatic approach. Figure https://www.ncbi.nlm.nih.gov/geo/) using the keywords: ((((rheumatoid arthritis[MeSH Terms]) OR rheumatoid arthritis) AND human[Organism]) AND Expression profiling by array[Filter]) AND (“2012/01/01” [Publication Date]: “2022/01/01” [Publication Date]). Exclusion criteria: (1) Excluded those with a small sample size (sample size < 20), (2) Excluded datasets that were irrelevant (it is not rheumatoid arthritis), (3) Excluded blood samples and/or cell samples, (4) Excluded samples with significant drug, vaccine, age, environmental, psychological, regional genetic, or epidemiological factors, and (5) Excluded samples lacking normal samples  using the keywords: ((((inflammatory bowel disease[MeSH Terms]) OR inflammatory bowel disease) AND human[Organism]) AND Expression profiling by array[Filter]) AND (“2012/01/01” [Publication Date]: “2022/01/01” [Publication Date]). Exclusion criteria: (1) Excluded those with a small sample size (sample size < 50), (2) Excluded datasets that were irrelevant (it is not inflammatory bowel disease), (3) Excluded impure mRNA or non-mRNA transcriptome datasets, (4) Excluded samples with significant drug, age, environmental, psychological, regional genetic, or epidemiological factors, (5) Excluded blood samples and/or cell samples, (6) Excluded samples lacking normal samples, (7) Excluded single disease datasets, and (8) Excluded datasets with ambiguous disease sample site types. Inclusion criteria (Novelty assessment): The one with the most recent publication date and the fewest studies on PubMed was selected based on the exclusion criteria  using the keywords: . Exclusion criteria: (1) Excluded datasets with 16 s rDNA, (2) Excluded datasets without publications in NCBI BioProjects  using the R package GEOquery25. Additionally, Homo sapiens samples for the GSE55235 and GSE55457 datasets were generated using the GPL96 [HG-U133A] Affymetrix Human Genome U133A Array platform; those for the GSE179285 dataset were generated using the Agilent 014850 Whole Human Genome Microarray 4 × 44 K G4112F (Probe Name version) platform; and those for the GSE77298 dataset were generated using the GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array platform. The GSE55235 dataset contained 10 synovial tissue samples from patients with RA and 10 samples from healthy individuals; the GSE55457 dataset contained 10 synovial tissue samples from healthy individuals and 13 samples from patients with RA; the GSE179285 dataset contained 14 inflamed colon tissue samples from patients with CD, 23 inflamed colon tissue samples from patients with UC, and 23 healthy colon tissue samples from healthy individuals; the GSE77298 dataset contained 16 synovial tissue samples from patients with RA and 7 samples from healthy individuals. The data from the GSE55235, GSE55457, and GSE77298 datasets were normalized using the RMA algorithm in the Affy package26 in R. The training set was created by merging the data from the GSE55235 and GSE55457 datasets, and the validation set was created using the data from the GSE77298 dataset. Additionally, the batch effects of the combined GSE55235 and GSE55457 datasets were removed using the Combat function of the sva package27. The principal component analysis (PCA) was used to evaluate the batch effect correction of the combined data28. Data from the GSE179285 dataset were downloaded, standardized, and analyzed using GEOquery25, Biobase29, and limma packages30. We used a distinct function of the “dplyr” package to remove the duplicate genes from each data set31. R software (version 4.3.0) was used for all data processing and analysis. Table The microarray datasets GSE5523532. The gene expression matrix is first entered into the R software to check for missing data and identify outliers. Next, we developed a scale-free network to select a soft threshold value for each disease, which is used as the parameter cut-off value for creating the adjacency and topology matrices. Next, gene co-expression modules for each disease were identified using the block modules function and module division analysis. Each module was associated with these diseases , and the Pearson correlation coefficients were used to filter the most relevant modules. The genes in these modules were classified as genes associated with diseases. Finally, the Venn diagram package33 was used to overlap module genes associated with RA, CD, and UC to screen for shared candidate genes.The analysis images of WGCNA are generated by R software. R software is open source software, and the various packages are free and open source.WGCNA is a standard method for processing large amounts of data that permits the grouping and modularization of a collection of genes most closely related to disease onset. The “WGCNA” R package was used in the study to build the gene co-expression networkhttps://string-db.org/)34. The string result table was then entered into Cytoscape35. We performed Degree analysis to predict important nodes (or hub genes) using Cytoscape’s cytoHubba plugin36.The PPI network of module genes for each disease was investigated using the interaction relation in the database STRING 34 database was used to construct a PPI network of the candidate genes. Additionally, GSEA was performed using the clusterProfiler package to analyze genes associated with RA, CD, and UC . The “c2.cp.kegg.v7.5.1.symbols.gmt” gene set was used to identify significantly enriched genes with a nominal false discovery rate (FDR) of < 0.25 and P < 0.05.The clusterProfiler package38 was performed using the glmnet package39 to identify genes in the RA training set. In addition, the SVM-RFE algorithm40 in the e1071 package41 was used to select genes. A Venn diagram was created using the machine learning mentioned above to further identify key genes by overlapping genes in the two modules. Immediately, a boxplot demonstrating the expression of these genes in the RA training set, CD dataset, and RA validation set was created using the ggplot242 and ggpubr43 packages. Furthermore, the function of these significant genes in the RA training set, CD dataset, UC dataset, and RA validation set was independently assessed by creating ROC curves in RStudio using the pROC package44. The shared specific genes in RA and IBD were selected as those with significant differences (P < 0.05) and AUC values of > 0.7 in all datasets.LASSO45 was retrieved from the GMrepo database (https://gmrepo.humangut.info/home)21. A total of 147 samples, including 92 samples from patients with RA and 55 samples from healthy individuals, were selected from the PRJEB6997 database. The limma package in R was used for analyzing the differential abundance of gut microbes. Bacteria with significantly differential abundance were selected based on |log2 FC| values of > 3 and P < 0.05. The ggplot2 and ggrepel46 packages in R were used to create a volcano map to demonstrate bacteria with differential abundance. LASSO was performed using the glmnet package to identify potential specific bacteria. Additionally, the SVM-RFE algorithm in the e1071 package was used to select potential specific bacteria. Subsequently, a Venn diagram was developed to identify the markers of gut microbiota by overlapping bacteria in the two modules of LASSO and SVM-RFE. To examine the relationship between the gut microbial markers and RA, the pROC package was used to analyze ROC curves in RStudio, and the ggplot2 and ggpubr packages were used to construct a boxplot in RStudio to compare gene expression among groups.The RA-related metagenomic sequencing dataset PRJEB6997http://bio-annotation.cn/gutmgene/)47 database was used to identify metabolites from the markers of gut microbiota. The STITCH database (http://stitch.embl.de/)48 was used to identify shared specific genes directly associated with these metabolites.The GutMGene (http://bio-annotation.cn/gutmgene/) database. The STITCH database (http://stitch.embl.de/) was used to investigate the link between metabolites and genes(including genes associated with pathways identified via GSEA and the shared specific genes related to the gut microbiome in RA), and the STRING (https://string-db.org/)34 database was used for analyzing the interaction between genes associated with pathways identified via GSEA and the shared specific genes related to the gut microbiome in RA. Finally, the Cytoscape35 program was being used to combine and display the previously indicated network links, resulting in an interaction network of shared specific genes related to the gut microbiome in RA, genes associated with pathways identified via GSEA, and the markers of the gut microbiome.Venn diagrams were constructed to overlap pathways identified via GSEA in the RA training set, CD dataset, UC dataset, and RA validation set and to overlap genes associated with these pathways in the RA training set, CD dataset, UC dataset, and RA validation set. The relationship between the metabolites and markers of gut microbiota was analyzed using the gutMGene . In the meanwhile, we quantified the infiltration abundances of the 24 immune cells (reported in earlier studies) in these samples using ssGSEA50 based on the R package “GSVA”51. Finally, the association between immune cell infiltration in the RA training set, CD dataset, UC dataset, and RA validation set and shared specific genes connected to the gut microbiota in RA was analyzed using Spearman analysis.We performed two immunoinvasive correlation analyses for this study. First, we combined the tagged genomes of several immune cell subpopulations in the CIBERSORTBefore analysis, batch effect reduction was applied to the GSE55235 and GSE55457 data sets (the RA training set), and PCA was used to evaluate and compare the features. Before the batch effect was removed, the data were dispersed as data sets, and it was visible  was set to 9  was set to 5  was set to 6  that were commonly identified using these two algorithms were selected    , whereas DUOX2 expressed poor discriminative efficiency (AUC < 0.7) .The RA training set was selected to screen for key genes between RA and IBD using two different machine learning algorithms. Of the 15 candidate genes, 4 were identified using the SVM-RFE algorithm Fig. A,B, and ted Fig. E. We pernce Fig. F; CXCL10.7) Fig. J. In thence Fig. G; CXCL10.7) Fig. K. In thence Fig. H; CXCL10.7) Fig. L. In thence Fig. I; CXCL10.7) Fig. M. The shPrevotella and Ruminococcus) and two intestinal microbes at the species (Prevotella copri and Ruminococcus bromii) levels in the PRJEB6997 dataset  identified using the two methods were selected   and species  levels. The gutMGene database was used to identify metabolites associated with the abovementioned microbes  (Supplementary Spreadsheet CXCL10) directly associated with the metabolites as the shared specific genes related to the gut microbiome in RA , 5 gut microbial groups identified at the species level , 14 metabolites  associated with the gut microbiome in RA, and the one shared specific gene related to the gut microbiome (CXCL10). This network contained 47 nodes and 231 edges  in the RA validation set , is an ELR-CXC chemokine54. It is mostly induced in humans when cell-mediated immune responses are elicited in pathological conditions such as infection, allograft rejection, and autoimmunity55. The expression of CXCL10 is very low in the colonic epithelium but substantially increases in colitis under the induction of IFN-γ57. Inhibiting CXCL10 reduces the frequency and severity of colitis and intestinal inflammation59. Additionally, patients with RA have higher CXCL10 expression in the synovial membrane60. High expression of CXCL10 mRNA and tissue infiltration of functional proteins in synovial tissue were also reported in CIA model rats with RA in a study on bone marrow mesenchymal stem cell therapy61. Increased CXCL10 mRNA has been observed in liver tissues of patients with HIV and HBV infection in various studies of inflammatory diseases, and its elevation is associated with disease activity62. Eldelumab , a human monoclonal antibody against CXCL10, has reportedly been developed and has demonstrated effectiveness in the treatment of RA and IBD64.66. Considering that the human intestinal microflora is affected by many factors such as region, population, host genetic factors, environment, and diet and different diseases may have different microbial flora, this study aimed to examine the relationship between the intestinal microflora in only one RA dataset and identify shared specific genes between IBD and RA. In the original study of the PRJEB6997 dataset, the abundance of Lactobacillus salivarius, Enterococcus, and Bacteroides was found to be high and that of Haemophilus, Klebsiella, and Bifidobacteria was found to be low in patients with RA45. In this study, the abundance of Prevotella was high and that of Ruminococcus and Ruminococcus bromii was low in patients with RA. It’s reported that the abundance of Prevotella copri was higher in stool samples of individuals with untreated new-onset RA (between 6 weeks and 6 months after diagnosis), and its presence was associated with a decline in the abundance of Bacteroides species and a loss of purportedly beneficial microbes2. Ruminococcus species can suppress TNF-α, and its abundance is lower in patients with Crohn’s disease than in healthy individuals68. On the contrary, Ruminococcus and Ruminococcus bromii are less reported in RA. In this study, data extracted from the gutMGene and STITCH databases revealed some metabolites associated with Ruminococcus, and succinate found in Ruminococcus champanellensis 18P13(T) had a direct relationship with CXCL10. A crucial metabolite in both host and microbial activities is succinate. Although succinate is typically considered an intermediate, it gets accumulated in some pathological conditions, especially during inflammation and metabolic stress69. Succinate was considered a pro-inflammatory metabolite; however, a study showed that it exerts anti-inflammatory effects on inflammatory signaling in macrophages70.Epidemiological and translational studies have suggested an interaction among bacteria in dysbiotic microbiota, and mucosal locations may play a causative role in the onset of RACXCL10 was significantly linked with the invasion of M1 macrophages in both RA and UC. Macrophages play an important role in RA. They are commonly found at the cartilage–pannus junction and in inflammatory synovial membranes. The extensive proinflammatory, destructive, and remodeling abilities of macrophages play an important role in both acute and chronic phases of RA71. TNF-α and interleukin-1 are two pro-inflammatory cytokines secreted by M1 macrophages, and several experimental and clinical studies have demonstrated their importance in the pathophysiology of RA73. Additionally, macrophages have been associated with IBD because they play a crucial role in several IBD-related risk genes75. Macrophages are regionally concentrated and polarize to the M1 subtype in UC, leading to persistent and recurrent inflammation78.Although this study had a relatively large sample size (GEO and GMrepo datasets), certain limitations should be noted. Clinical samples should be used to validate these findings. Owing to clinical research and ethical constraints, the present study was not completely rigorous. Moreover, this study focused on the relationship between intestinal microbiota and genes. However, it is challenging to collect or monitor the intestinal microbiota of a single patient at the same time, as the intestinal microbiota may change owing to various factors such as environmental change or growth and development. The use of microarray technology to evaluate gene expression presents another drawback. Since fluorescence-mediated gene expression assessment is a biased method in contrast to hypothesis-free sequencing technology, RNA sequencing is more frequently used for assessing broad gene expression than microarray. Furthermore, even if we attempted to eliminate the batch impact of the combined data using the combat function of the sva package, it is undeniable that any solution can only mitigate this effect. These important issues should be considered in future studies.CXCL10 is involved in the onset of RA and IBD, it can be used to diagnose these two conditions. In addition, the gut microbiome in RA and several pathways related to IBD and RA were also found to be regulated by CXCL10. The findings of this study revealed the mechanism underlying the association between RA and IBD and served as a reference for further investigation of the intestinal flora in RA.In conclusion, because Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.Supplementary Information 6.Supplementary Information 7.Supplementary Information 8.Supplementary Information 9.Supplementary Information 10.Supplementary Information 11.Supplementary Information 12.Supplementary Information 13.Supplementary Information 14.Supplementary Information 15.