Deep learning-driven adaptive optics for single-molecule localization microscopy.

The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.

Slide-free clinical imaging of melanin with absolute quantities using label-free third-harmonic-generation enhancement-ratio microscopy.

The capability to image the 3D distribution of melanin in human skin in vivo with absolute quantities and microscopic details will not only enable noninvasive histopathological diagnosis of melanin-related cutaneous disorders, but also make long term treatment assessment possible. In this paper, we demonstrate clinical in vivo imaging of the melanin distribution in human skin with absolute quantities on mass density and with microscopic details by using label-free third-harmonic-generation (THG) enhancement-ratio microscopy. As the dominant absorber in skin, melanin provides the strongest THG nonlinearity in human skin due to resonance enhancement. We show that the THG-enhancement-ratio (erTHG) parameter can be calibrated in vivo and can indicate the melanin mass density. With an unprecedented clinical imaging resolution, our study revealed erTHG-microscopy's unique capability for long-term treatment assessment and direct clinical observation of melanin's micro-distribution to shed light into the unknown pathway and regulation mechanism of melanosome transfer and translocation.

Pilot clinical study to investigate the human whole blood spectrum characteristics in the sub-THz region.

We have conducted a pilot clinical study to not only investigate the sub-THz spectra of ex-vivo fresh human whole blood of 28 patients following 8-hours fasting guideline, but also to find out the critical blood ingredients of which the concentration dominantly affects those sub-THz spectra. A great difference between the sub-THz absorption properties of human blood among different people was observed, while the difference can be up to ~15% of the averaged absorption coefficient of the 28 samples. Our pilot clinical study indicates that triglycerides and the number of red blood cells were two dominant factors to have significant negative correlation to the sub-THz absorption coefficients.

[Gynecologic cancers in a hospital: a retrospective analysis of admission data over ten years].

OBJECTIVE: To investigate admission patterns of patients with gynecologic cancers over a ten year period, which will provide a basis for further epidemiological studies. METHODS: We reviewed medical records of patients with gynecologic cancers who were admitt d to the West China Second University Hospital of Sichuan University from 2003 to 2012. Their clinicopathological data were extracted and analysed. RESULTS: The number of admitted patients increased over the years, with cervical, uterine and ovary cancers as the top three gynaecological cancers. They accounted for 92.13% of total gynaecological cancers. The peak age of gynaecological cancers was 40-49 years, which accounted for 34.02% (3132/9207) of all patients, followed by 50-59 years (26.64%, 2453/9207). Most (72.46%, 3062/4226) cervical cancer patients aged 30-49 years, compared with 40-59 years for uterine cancers (69.77%, 1768/2534) and 40-59 years for ovarian cancers (58.30%, 1004/1722). Patients in their 20th account for 4.43% (408/9 207) of total cancers, with in which cervical and ovarian cancers as the most common pathological type. Patients under 20 years of age accounted for only 0.98% (90/9207) of total cancers, with ovarian cancers as the most common pathological type. Patients over 60 years accounted for 12.90% (1188/9207) of total cancers, with uterine and ovarian cancers as the most common pathological type. Most patients were at an early stage of cancers when they were admitted to the hospital. CONCLUSION: Hospitalized patients with gynecologic cancers increase over years. Cervical, uterine and ovary cancers remain to be a focus of treatment. Peak age of those cancers varies.