Label-Free Monitoring of Endometrial Cancer Progression Using Multiphoton Microscopy.

Endometrial cancer is the most common gynecological cancer in the developed world. However, the accuracy of current diagnostic methods is still unsatisfactory and time-consuming. Here, we presented an alternate approach to monitoring the progression of endometrial cancer via multiphoton microscopy imaging and analysis of collagen, which is often overlooked in current endometrial cancer diagnosis protocols but can offer a crucial signature in cancer biology. Multiphoton microscopy (MPM) based on the second-harmonic generation and two-photon excited fluorescence was introduced to visualize the microenvironment of endometrium in normal, hyperplasia without atypia, atypical hyperplasia, and endometrial cancer specimens. Furthermore, automatic image analysis based on the MPM image processing algorithm was used to quantify the differences in the collagen morphological features among them. MPM enables the visualization of the morphological details and alterations of the glands in the development process of endometrial cancer, including irregular changes in the structure of the gland, increased ratio of the gland to the interstitium, and atypical changes in the glandular epithelial cells. Moreover, the destructed basement membrane caused by gland proliferation and fusion is clearly shown in SHG images, which is a key feature for identifying endometrial cancer progression. Quantitative analysis reveals that the formation of endometrial cancer is accompanied by an increase in collagen fiber length and width, a progressive linearization and loosening of interstitial collagen, and a more random arrangement of interstitial collagen. Observation and quantitative analysis of interstitial collagen provide invaluable information in monitoring the progression of endometrial cancer. Label-free multiphoton imaging reported here has the potential to become an in situ histological tool for effective and accurate early diagnosis and detection of malignant lesions in endometrial cancer.

Selection of functional sperm by using hyaluronic acid modified magnetic microbeads and an electromagnetic manipulation system.

In recent years, the incidence of infertility has increased year by year. Assisted reproductive technology (ART) is one of the effective strategies to treat infertility. In the process of ART, commonly used methods for sperm separation have shortcomings and there is still room for improvement. In this study, a functional sperm selection strategy was established based on hyaluronic acid (HA) modified magnetic microbeads (MBs) and a supporting two-dimensional electromagnetic manipulation device system. Due to the modification of HA on the surface of MBs, the HA-MBs have the ability to target and bind to specific receptors on the sperm membrane to form a sperm-MB complex. A disulfide linker was introduced to connect HA and MBs. After modifying HA and connecting it with the disulfide linker, the sperm of sperm-MBs can be released under the combined effect of hyaluronidase and reduced GSH with the disulfide bond broken and HA degraded. A two-dimensional electromagnetic manipulation system was introduced to generate a magnetic field and control the directional movement of the sperm-MB complex under the guidance of an inverted microscope. The free MBs can also be removed after the sperm is released. Furthermore, the mouse sperm selected through this strategy can achieve normal insemination via ICSI and the obtained blastocysts have normal morphology and developmental milestones. This strategy has potential to be developed into an automated screening solution for the screening of functional sperm for assisted reproductive technology.

Cervical cytology screening facilitated by an artificial intelligence microscope: A preliminary study.

BACKGROUND: Cervical cytology screening is usually laborious with a heavy workload and poor diagnostic consistency. The authors have developed an artificial intelligence (AI) microscope that can provide onsite diagnostic assistance for cervical cytology screening in real time. METHODS: A total of 2167 cervical cytology slides were selected from a cohort of 10,601 cases from Shenzhen Maternity and Child Healthcare Hospital, and the training data set consisted of 42,073 abnormal cervical epithelial cells. The recognition results of an AI technique were presented in a microscope eyepiece by an augmented reality technique. Potentially abnormal cells were highlighted with binary classification results in a 10× field of view (FOV) and with multiclassification results according to the Bethesda system in 20× and 40× FOVs. In addition, 486 slides were selected for the reader study to evaluate the performance of the AI microscope. RESULTS: In the reader study, which compared manual reading with AI assistance, the sensitivities for the detection of low-grade squamous intraepithelial lesions and high-grade squamous intraepithelial lesions were significantly improved from 0.837 to 0.923 (P < .001) and from 0.830 to 0.917 (P < .01), respectively; the κ score for atypical squamous cells of undetermined significance (ASCUS) was improved from 0.581 to 0.637; the averaged pairwise κ of consistency for multiclassification was improved from 0.649 to 0.706; the averaged pairwise κ of consistency for binary classification was improved from 0.720 to 0.798; and the averaged pairwise κ of ASCUS was improved from 0.557 to 0.639. CONCLUSIONS: The results of this study show that an AI microscope can provide real-time assistance for cervical cytology screening and improve the efficiency and accuracy of cervical cytology diagnosis.

The Utility of Comprehensive Metabolic Panel Tests for the Prediction of Bronchopulmonary Dysplasia in Extremely Premature Infants.

BACKGROUND: Comprehensive metabolic panel tests (CMP) are routinely performed in extremely premature infants within the first days of life. The association between the parameters of first postnatal CMP and the risk of bronchopulmonary dysplasia (BPD) remains elusive. METHODS: A retrospective analysis was performed to evaluate the correlation between the parameters of first postnatal CMP and the risk of BPD in a cohort of extremely premature infants (born with a gestational age less than 28 weeks or a birth weight less than 1000 grams) at the neonatal intensive care unit, Shenzhen Maternity and Child Healthcare Hospital, from January 2016 to October 2018. A multivariant regression model was built to assess the association of the first postnatal CMP with the development of BPD. RESULTS: A total of 256 extremely premature infants were included in this study. BPD developed in 76 (29.7%) infants. The first CMP in these infants was performed at 5 to 8 days after birth. The levels of blood urea nitrogen (BUN) and magnesium were significantly higher in infants with BPD compared to infants with no BPD (10.2 versus 7.5 mmol/L, P < 0.001 and 0.9 versus 0.8 U/L, P = 0.001, respectively) whereas the level of alkaline phosphatase (ALP) and total protein was significantly lower in infants with BPD (215.5 versus 310.0 U/L, P = 0.002 and 41.2 versus 42.9 g/L, P = 0.037, respectively). Multiple analysis showed that a higher level of BUN (>8.18 mmol/L) was independently associated with BPD (OR 3.261, 95% CI 1.779-5.978). CONCLUSION: Our findings indicate that a higher postnatal BUN level (>8.18 mmol/L) may be a predictor for the development of BPD in extremely premature infants.