Two-photon excitation laser scanning microscopy (TPM) was used to image human, porcine, and rabbit nasal septal cartilage. TPM provides optical sections of thick tissue specimens in situ without the use of exogenous dyes or need for tissue fixation. The cartilage tissue was imaged using near-infrared light generated by a mode-locked titanium/sapphire laser that was raster-scanned and coupled to an inverted microscope. Absorption of two photons by endogenous molecules and subsequent fluorescence was filtered to specific spectral bandwidths and detected with photomultiplier tubes. Two-photon stimulated fluorescence was detected with photomultiplier tubes optimized to specific spectral bandwidths. Signal intensity corresponds to the concentration of fluorophores, principally NADH, NADPH, and flavoproteins hence providing a means of redox imaging the cellular metabolic state. Specimens were scanned from the surface to a depth of about 150 microm. Image size was 50 x 50 microm with a diffraction limited pixel size of 0.4 microm. Cell membranes, nuclei, and matrix structures were identified in human, pig, and rabbit tissues. TPM provides a means to study three dimensional chondrocyte structure and matrix organization in situ at substantial depths, and permits longitudinal examination of cultured tissue explants without the need for exogenous dyes, tissue preparation, or fixation.

Objective

To assess the ability of nonlinear optical microscopy (NLOM) to image ex vivo healthy and degenerative bovine articular cartilage.

Method

Fresh bovine femoral-tibial joints were obtained from an abattoir. Articular cartilage specimens were harvested from the tibial plateau. Normal and degenerative specimens were imaged by NLOM and subsequently fixed and processed for histological examination.

Results

NLOM provided high resolution images of articular cartilage at varying depths with high sensitivity to tissue morphology and high specificity to tissue components without fixing, sectioning or staining. Spectroscopic segmentation of nonlinear optical signals isolated the collagen matrix from the chondron (chondrocyte and non-collagen pericellular matrix). Images from the superficial zone were consistent with the presence of a matrix composed of both elastin-like and collagen fibers distributed in a depth-dependent morphological arrangement, whereas only collagen was demonstrated in the middle and deep zones. Alterations of collagen matrix associated with advanced degenerative joint disease (fibrocartilage) were observed with NLOM. Individual chondrocytes were imaged and demonstrated intracellular fluorescence consistent with the presence of products of intracellular biochemical processes.

Conclusion

Thin images of living articular cartilage using NLOM may be obtained with (sub-)cellular resolution at varying depths without fixing, sectioning or staining. Extracellular matrical collagen and chondron may be imaged separately in native tissue using spectrally distinct, endogenous, nonlinear optical signals. NLOM was sensitive to macromolecular composition and pathologic changes in articular cartilage matrix. Advances in instrumentation may lead to the application of NLOM to study articular cartilage in vivo.

Instructor Talk-noncontent language used by instructors in classrooms-is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk framework to noncontent language used by instructors in novel course contexts. We analyzed Instructor Talk in eight additional biology courses in their entirety and in 61 biology courses using an emergent sampling strategy. We observed widespread use of Instructor Talk with variation in the amount and category type used. The vast majority of Instructor Talk could be characterized using the originally published Instructor Talk framework, suggesting the robustness of this framework. Additionally, a new form of Instructor Talk-Negatively Phrased Instructor Talk, language that may discourage students or distract from the learning process-was detected in these novel course contexts. Finally, the emergent sampling strategy described here may allow investigation of Instructor Talk in even larger numbers of courses across institutions and disciplines. Given its widespread use, potential influence on students in learning environments, and ability to be sampled, Instructor Talk may be a key variable to consider in future research on teaching and learning in higher education.

Active-learning pedagogies have been repeatedly demonstrated to produce superior learning gains with large effect sizes compared with lecture-based pedagogies. Shifting large numbers of college science, technology, engineering, and mathematics (STEM) faculty to include any active learning in their teaching may retain and more effectively educate far more students than having a few faculty completely transform their teaching, but the extent to which STEM faculty are changing their teaching methods is unclear. Here, we describe the development and application of the machine-learning-derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers. DART analyzes the volume and variance of classroom recordings to predict the quantity of time spent on single voice (e.g., lecture), multiple voice (e.g., pair discussion), and no voice (e.g., clicker question thinking) activities. Applying DART to 1,486 recordings of class sessions from 67 courses, a total of 1,720 h of audio, revealed varied patterns of lecture (single voice) and nonlecture activity (multiple and no voice) use. We also found that there was significantly more use of multiple and no voice strategies in courses for STEM majors compared with courses for non-STEM majors, indicating that DART can be used to compare teaching strategies in different types of courses. Therefore, DART has the potential to systematically inventory the presence of active learning with ∼90% accuracy across thousands of courses in diverse settings with minimal effort.

Many efforts to improve science teaching in higher education focus on a few faculty members at an institution at a time, with limited published evidence on attempts to engage faculty across entire departments. We created a long-term, department-wide collaborative professional development program, Biology Faculty Explorations in Scientific Teaching (Biology FEST). Across 3 years of Biology FEST, 89% of the department's faculty completed a weeklong scientific teaching institute, and 83% of eligible instructors participated in additional semester-long follow-up programs. A semester after institute completion, the majority of Biology FEST alumni reported adding active learning to their courses. These instructor self-reports were corroborated by audio analysis of classroom noise and surveys of students in biology courses on the frequency of active-learning techniques used in classes taught by Biology FEST alumni and nonalumni. Three years after Biology FEST launched, faculty participants overwhelmingly reported that their teaching was positively affected. Unexpectedly, most respondents also believed that they had improved relationships with departmental colleagues and felt a greater sense of belonging to the department. Overall, our results indicate that biology department-wide collaborative efforts to develop scientific teaching skills can indeed attract large numbers of faculty, spark widespread change in teaching practices, and improve departmental relations.