Protein Based Biomaterials for Therapeutic and Diagnostic Applications.

Proteins are some of the most versatile and studied macromolecules with extensive biomedical applications. The natural and biological origin of proteins offer such materials several advantages over their synthetic counterparts, such as innate bioactivity, recognition by cells and reduced immunogenic potential. Furthermore, proteins can be easily functionalized by altering their primary amino acid sequence and can often be further self-assembled into higher order structures either spontaneously or under specific environmental conditions. This review will feature the recent advances in protein-based biomaterials in the delivery of therapeutic cargo such as small molecules, genetic material, proteins, and cells. First, we will discuss the ways in which secondary structural motifs, the building blocks of more complex proteins, have unique properties that enable them to be useful for therapeutic delivery. Next, supramolecular assemblies, such as fibers, nanoparticles, and hydrogels, made from these building blocks that are engineered to behave in a cohesive manner, are discussed. Finally, we will cover additional modifications to protein materials that impart environmental responsiveness to materials. This includes the emerging field of protein molecular robots, and relatedly, protein-based theranostic materials that combine therapeutic potential with modern imaging modalities, including near-infrared fluorescence spectroscopy (NIRF), single-photo emission computed tomography/computed tomography (SPECT/CT), positron emission tomography (PET), magnetic resonance imaging (MRI), and ultrasound/photoacoustic imaging (US/PAI).

Altered Food Habits? Understanding the Feeding Preference of Free-Ranging Gray Langurs Within an Urban Settlement.

Urbanization affects concurrent human-animal interactions as a result of altered resource availability and land use pattern, which leads to considerable ecological consequences. While some animals have lost their habitat due to urban encroachment, few of them managed to survive within the urban ecosystem by altering their natural behavioral patterns. The feeding repertoire of folivorous colobines, such as gray langur, largely consists of plant parts. However, these free-ranging langurs tend to be attuned to the processed high-calorie food sources to attain maximum benefits within the concrete jungle having insignificant greenery. Therefore, besides understanding their population dynamics, the effective management of these urbanized, free-ranging, non-human primate populations also depends on their altered feeding habits. Here, we have used a field-based experimental setup that allows gray langurs to choose between processed and unprocessed food options, being independent of any inter-specific conflicts over resources due to food scarcity. The multinomial logit model reveals the choice-based decision-making of these free-ranging gray langurs in an urban settlement of West Bengal, India, where they have not only learned to recognize the human-provisioned processed food items as an alternative food source but also shown a keen interest in it. However, such a mismatch between the generalized feeding behavior of folivorous colobines and their specialized gut physiology reminds us of Liem's paradox and demands considerable scientific attention. While urbanization imposes tremendous survival challenges to these animals, it also opens up for various alternative options for surviving in close proximity to humans which is reflected in this study, and could guide us for the establishment of a sustainable urban ecosystem in the future.

Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks.

Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times of activation (motifs) emerge from anatomically accurate feed-forward connections from DG through tunnels to CA3.

Combined spectral and temporal enhancement to improve cochlear-implant speech perception.

The present study examined the effect of combined spectral and temporal enhancement on speech recognition by cochlear-implant (CI) users in quiet and in noise. The spectral enhancement was achieved by expanding the short-term Fourier amplitudes in the input signal. Additionally, a variation of the Transient Emphasis Spectral Maxima (TESM) strategy was applied to enhance the short-duration consonant cues that are otherwise suppressed when processed with spectral expansion. Nine CI users were tested on phoneme recognition tasks and ten CI users were tested on sentence recognition tasks both in quiet and in steady, speech-spectrum-shaped noise. Vowel and consonant recognition in noise were significantly improved with spectral expansion combined with TESM. Sentence recognition improved with both spectral expansion and spectral expansion combined with TESM. The amount of improvement varied with individual CI users. Overall the present results suggest that customized processing is needed to optimize performance according to not only individual users but also listening conditions.

Companding to improve cochlear-implant speech recognition in speech-shaped noise.

Nonlinear sensory and neural processing mechanisms have been exploited to enhance spectral contrast for improvement of speech understanding in noise. The "companding" algorithm employs both two-tone suppression and adaptive gain mechanisms to achieve spectral enhancement. This study implemented a 50-channel companding strategy and evaluated its efficiency as a front-end noise suppression technique in cochlear implants. The key parameters were identified and evaluated to optimize the companding performance. Both normal-hearing (NH) listeners and cochlear-implant (CI) users performed phoneme and sentence recognition tests in quiet and in steady-state speech-shaped noise. Data from the NH listeners showed that for noise conditions, the implemented strategy improved vowel perception but not consonant and sentence perception. However, the CI users showed significant improvements in both phoneme and sentence perception in noise. Maximum average improvement for vowel recognition was 21.3 percentage points (p<0.05) at 0 dB signal-to-noise ratio (SNR), followed by 17.7 percentage points (p<0.05) at 5 dB SNR for sentence recognition and 12.1 percentage points (p<0.05) at 5 dB SNR for consonant recognition. While the observed results could be attributed to the enhanced spectral contrast, it is likely that the corresponding temporal changes caused by companding also played a significant role and should be addressed by future studies.