POCUS for Thrombus: Emphasizing the Importance of Initial Point-of-Care Ultrasound in the Management of Pulmonary Thromboembolism.

Pulmonary embolism (PE) constitutes a substantial health burden among individuals in the United States. It ranks as the third most common cause of cardiovascular death aside from stroke and myocardial infarction. Diagnostic errors are common with PE as patients can present with non-specific symptoms or could be completely asymptomatic with PE being an incidental finding. Diagnostic errors can result in missed or late diagnosis of PE, which, in turn, increases health care costs, morbidity, and mortality rates. Hence, early diagnosis is crucial. Computed tomography pulmonary angiography (CTPA) remains the gold standard in PE diagnosis, despite exposure to high doses of radiation. Point-of-care ultrasound (POCUS) is an underutilized, non-invasive technique that aids in the early diagnosis of PE and can safely reduce the radiation from CTPA in cases where contraindication exists. POCUS has been shown to have a high sensitivity and specificity for early diagnosis of PE.

Genetic association analysis of human median voice pitch identifies a common locus for tonal and non-tonal languages.

The genetic influence on human vocal pitch in tonal and non-tonal languages remains largely unknown. In tonal languages, such as Mandarin Chinese, pitch changes differentiate word meanings, whereas in non-tonal languages, such as Icelandic, pitch is used to convey intonation. We addressed this question by searching for genetic associations with interindividual variation in median pitch in a Chinese major depression case-control cohort and compared our results with a genome-wide association study from Iceland. The same genetic variant, rs11046212-T in an intron of the ABCC9 gene, was one of the most strongly associated loci with median pitch in both samples. Our meta-analysis revealed four genome-wide significant hits, including two novel associations. The discovery of genetic variants influencing vocal pitch across both tonal and non-tonal languages suggests the possibility of a common genetic contribution to the human vocal system shared in two distinct populations with languages that differ in tonality (Icelandic and Mandarin).

A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from Speech.

The proposed method focuses on speaker disentanglement in the context of depression detection from speech signals. Previous approaches require patient/speaker labels, encounter instability due to loss maximization, and introduce unnecessary parameters for adversarial domain prediction. In contrast, the proposed unsupervised approach reduces cosine similarity between latent spaces of depression and pre-trained speaker classification models. This method outperforms baseline models, matches or exceeds adversarial methods in performance, and does so without relying on speaker labels or introducing additional model parameters, leading to a reduction in model complexity. The higher the speaker de-identification score (DeID), the better the depression detection system is in masking a patient's identity thereby enhancing the privacy attributes of depression detection systems. On the DAIC-WOZ dataset with ComparE16 features and an LSTM-only model, our method achieves an F1-Score of 0.776 and a DeID score of 92.87%, outperforming its adversarial counterpart which has an F1Score of 0.762 and 68.37% DeID, respectively. Furthermore, we demonstrate that speaker-disentanglement methods are complementary to text-based approaches, and a score-level fusion with a Word2vec-based depression detection model further enhances the overall performance to an F1-Score of 0.830.

Enhancing accuracy and privacy in speech-based depression detection through speaker disentanglement.

Speech signals are valuable biomarkers for assessing an individual's mental health, including identifying Major Depressive Disorder (MDD) automatically. A frequently used approach in this regard is to employ features related to speaker identity, such as speaker-embeddings. However, over-reliance on speaker identity features in mental health screening systems can compromise patient privacy. Moreover, some aspects of speaker identity may not be relevant for depression detection and could serve as a bias factor that hampers system performance. To overcome these limitations, we propose disentangling speaker-identity information from depression-related information. Specifically, we present four distinct disentanglement methods to achieve this - adversarial speaker identification (SID)-loss maximization (ADV), SID-loss equalization with variance (LEV), SID-loss equalization using Cross-Entropy (LECE) and SID-loss equalization using KL divergence (LEKLD). Our experiments, which incorporated diverse input features and model architectures, have yielded improved F1 scores for MDD detection and voice-privacy attributes, as quantified by Gain in Voice Distinctiveness GV D and De-Identification Scores (DeID). On the DAIC-WOZ dataset (English), LECE using ComparE16 features results in the best F1-Scores of 80% which represents the audio-only SOTA depression detection F1-Score along with a GV D of -1.1 dB and a DeID of 85%. On the EATD dataset (Mandarin), ADV using raw-audio signal achieves an F1-Score of 72.38% surpassing multi-modal SOTA along with a GV D of -0.89 dB dB and a DeID of 51.21%. By reducing the dependence on speaker-identity-related features, our method offers a promising direction for speech-based depression detection that preserves patient privacy.

Non-uniform Speaker Disentanglement For Depression Detection From Raw Speech Signals.

While speech-based depression detection methods that use speaker-identity features, such as speaker embeddings, are popular, they often compromise patient privacy. To address this issue, we propose a speaker disentanglement method that utilizes a non-uniform mechanism of adversarial SID loss maximization. This is achieved by varying the adversarial weight between different layers of a model during training. We find that a greater adversarial weight for the initial layers leads to performance improvement. Our approach using the ECAPA-TDNN model achieves an F1-score of 0.7349 (a 3.7% improvement over audio-only SOTA) on the DAIC-WoZ dataset, while simultaneously reducing the speaker-identification accuracy by 50%. Our findings suggest that identifying depression through speech signals can be accomplished without placing undue reliance on a speaker's identity, paving the way for privacy-preserving approaches of depression detection.

Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals.

Major Depressive Disorder (MDD) is a severe illness that affects millions of people, and it is critical to diagnose this disorder as early as possible. Detecting depression from voice signals can be of great help to physicians and can be done without any invasive procedure. Since relevant labelled data are scarce, we propose a modified Instance Discriminative Learning (IDL) method, an unsupervised pre-training technique, to extract augment-invariant and instance-spread-out embeddings. In terms of learning augment-invariant embeddings, various data augmentation methods for speech are investigated, and time-masking yields the best performance. To learn instance-spreadout embeddings, we explore methods for sampling instances for a training batch (distinct speaker-based and random sampling). It is found that the distinct speaker-based sampling provides better performance than the random one, and we hypothesize that this result is because relevant speaker information is preserved in the embedding. Additionally, we propose a novel sampling strategy, Pseudo Instance-based Sampling (PIS), based on clustering algorithms, to enhance spread-out characteristics of the embeddings. Experiments are conducted with DepAudioNet on DAIC-WOZ (English) and CONVERGE (Mandarin) datasets, and statistically significant improvements, with p-value 0.0015 and 0.05, respectively, are observed using PIS in the detection of MDD relative to the baseline without pre-training.

A Step Towards Preserving Speakers' Identity While Detecting Depression Via Speaker Disentanglement.

Preserving a patient's identity is a challenge for automatic, speech-based diagnosis of mental health disorders. In this paper, we address this issue by proposing adversarial disentanglement of depression characteristics and speaker identity. The model used for depression classification is trained in a speaker-identity-invariant manner by minimizing depression prediction loss and maximizing speaker prediction loss during training. The effectiveness of the proposed method is demonstrated on two datasets - DAIC-WOZ (English) and CONVERGE (Mandarin), with three feature sets (Mel-spectrograms, raw-audio signals, and the last-hidden-state of Wav2vec2.0), using a modified DepAudioNet model. With adversarial training, depression classification improves for every feature when compared to the baseline. Wav2vec2.0 features with adversarial learning resulted in the best performance (F1-score of 69.2% for DAIC-WOZ and 91.5% for CONVERGE). Analysis of the class-separability measure (J-ratio) of the hidden states of the DepAudioNet model shows that when adversarial learning is applied, the backend model loses some speaker-discriminability while it improves depression-discriminability. These results indicate that there are some components of speaker identity that may not be useful for depression detection and minimizing their effects provides a more accurate diagnosis of the underlying disorder and can safeguard a speaker's identity.

FRAUG: A FRAME RATE BASED DATA AUGMENTATION METHOD FOR DEPRESSION DETECTION FROM SPEECH SIGNALS.

In this paper, a data augmentation method is proposed for depression detection from speech signals. Samples for data augmentation were created by changing the frame-width and the frame-shift parameters during the feature extraction process. Unlike other data augmentation methods (such as VTLP, pitch perturbation, or speed perturbation), the proposed method does not explicitly change acoustic parameters but rather the time-frequency resolution of frame-level features. The proposed method was evaluated using two different datasets, models, and input acoustic features. For the DAIC-WOZ (English) dataset when using the DepAudioNet model and mel-Spectrograms as input, the proposed method resulted in an improvement of 5.97% (validation) and 25.13% (test) when compared to the baseline. The improvements for the CONVERGE (Mandarin) dataset when using the x-vector embeddings with CNN as the backend and MFCCs as input features were 9.32% (validation) and 12.99% (test). Baseline systems do not incorporate any data augmentation. Further, the proposed method outperformed commonly used data-augmentation methods such as noise augmentation, VTLP, Speed, and Pitch Perturbation. All improvements were statistically significant.

Deltamethrin modulates the native structure of Hen Egg White Lysozyme and induces its aggregation at physiological pH.

Deltamethrin, a type II pyrethroid pesticide was initially considered as safe for human use. Recent studies have reported several pathophysiological effects of deltamethrin on human and non-human species. However, its effect on structure and function of protein leading to progressive neurodegeneration is poorly understood. In present study, we investigated the interaction of deltamethrin with Hen Egg White Lysozyme (HEWL) at physiological pH and tried to understand the effect of pesticide on structure and function of protein. Employing different biophysical techniques, we shown that deltamethrin induces in vitro aggregation of HEWL in concentration dependent manner. Interaction of pesticide with different amino acids, followed by exposure of hydrophobic regions was driving force of aggregation process. Apart from modulating the hydrophobic domain, deltamethrin is observed to reduce α-helical and promote ß-sheet content of lysozyme, eventually converting the globular protein into ThT sensitive amyloid fibrils and amorphous aggregates. Our study also indicate that deltamethrin induced aggregation reduces the catalytic activity of lysozyme.

Time-Resolved Far Infrared Light Transport Decomposition for Thermal Photometric Stereo.

We present a novel time-resolved light transport decomposition method using thermal imaging. Because the speed of heat propagation is much slower than the speed of light propagation, the transient transport of far infrared light can be observed at a video frame rate. A key observation is that the thermal image looks similar to the visible light image in an appropriately controlled environment. This implies that conventional computer vision techniques can be straightforwardly applied to the thermal image. We show that the diffuse component in the thermal image can be separated, and therefore, the surface normals of objects can be estimated by the Lambertian photometric stereo. The effectiveness of our method is evaluated by conducting real-world experiments, and its applicability to black body, transparent, and translucent objects is shown.

Bacopa monnieri inhibit hen egg white lysozyme fibrillation and help in retaining its activity at acidic condition.

Inhibiting protein misfolding and aggregation is crucial for the treatment of several amyloidoses. Though various types of synthetic drugs are being explored as therapeutic agents, herbal extracts are better alternative owing to their natural origin, higher bioavailability and improved biosafety characteristics. In the present study, we demonstrate that night long (∼12 hr) preincubation of hen egg white lysozyme (HEWL) with Bacopa monnieri (brahmi) at neutral pH, impede the aggregation and fibrillation of protein at pH 2.0. Employing different biophysical techniques such as static and dynamic light scattering, Thioflavin T (ThT) assay, sedimentation assay and atomic force microscopy (AFM), we show that brahmi inhibit the HEWL aggregation in concentration dependent manner. 8-anilino-1-naphthalene sulfonate (ANS) fluorescence reveals that brahmi masks the exposure of hydrophobic domain of lysozyme. Significant recovery of enzymatic activity of HEWL in the presence of brahmi at pH 2.0 is salient feature of this work. Nearly 90% recovery of catalytic activity of lysozyme after 216 hr (9 days) of incubation indicate that interaction of HEWL-brahmi stabilizes the native structure of protein thus enhancing the activation energy barrier for protein misfolding and subsequent aggregation. Our findings show that brahmi could be promising alternative for the therapies of several protein misfolding disorders.Communicated by Ramaswamy H. Sarma.

Structural perturbation by arsenic triggers the aggregation of hen egg white lysozyme by promoting oligomers formation.

Arsenic trioxide is one of the most common metallic pollutants entering the food chain both by human activities and nature. Its entry inside the living organism through food, air and water results into the accumulation of heavy metal in several tissues which manifest several metabolic or hormonal disorders. Till now the effect of arsenic trioxide on protein misfolding and aggregation culminating into several neurodegenerative disorders is poorly understood. In the present study, we reveal the aggregation process of Hen Egg White Lysozyme (HEWL) in presence of arsenic trioxide (As2O3) at physiological conditions. We show that As2O3 promote the in vitro aggregation of HEWL in concentration dependent manner. Early phase of aggregation is observed to be induced by exposure of hydrophobic surfaces which later reorganized to promote further self-association leading to ß sheet structure. Presence of lower ordered oligomers after two days and higher ordered oligomers along with amorphous aggregates after week long incubation indicate that As2O3 drives the self-assembly of lysozyme towards oligomeric form.

A galactose-functionalized dendritic siRNA-nanovector to potentiate hepatitis C inhibition in liver cells.

A RNAi based antiviral strategy holds the promise to impede hepatitis C viral (HCV) infection overcoming the problem of emergence of drug resistant variants, usually encountered in the interferon free direct-acting antiviral therapy. Targeted delivery of siRNA helps minimize adverse 'off-target' effects and maximize the efficacy of therapeutic response. Herein, we report the delivery of siRNA against the conserved 5'-untranslated region (UTR) of HCV RNA using a liver-targeted dendritic nano-vector functionalized with a galactopyranoside ligand (DG). Physico-chemical characterization revealed finer details of complexation of DG with siRNA, whereas molecular dynamic simulations demonstrated sugar moieties projecting "out" in the complex. Preferential delivery of siRNA to the liver was achieved through a highly specific ligand-receptor interaction between dendritic galactose and the asialoglycoprotein receptor. The siRNA-DG complex exhibited perinuclear localization in liver cells and co-localization with viral proteins. The histopathological studies showed the systemic tolerance and biocompatibility of DG. Further, whole body imaging and immunohistochemistry studies confirmed the preferential delivery of the nucleic acid to mice liver. Significant decrease in HCV RNA levels (up to 75%) was achieved in HCV subgenomic replicon and full length HCV-JFH1 infectious cell culture systems. The multidisciplinary approach provides the 'proof of concept' for restricted delivery of therapeutic siRNAs using a target oriented dendritic nano-vector.

Preventing disulfide bond formation weakens non-covalent forces among lysozyme aggregates.

Nonnative disulfide bonds have been observed among protein aggregates in several diseases like amyotrophic lateral sclerosis, cataract and so on. The molecular mechanism by which formation of such bonds promotes protein aggregation is poorly understood. Here in this work we employ previously well characterized aggregation of hen eggwhite lysozyme (HEWL) at alkaline pH to dissect the molecular role of nonnative disulfide bonds on growth of HEWL aggregates. We employed time-resolved fluorescence anisotropy, atomic force microscopy and single-molecule force spectroscopy to quantify the size, morphology and non-covalent interaction forces among the aggregates, respectively. These measurements were performed under conditions when disulfide bond formation was allowed (control) and alternatively when it was prevented by alkylation of free thiols using iodoacetamide. Blocking disulfide bond formation affected growth but not growth kinetics of aggregates which were ∼50% reduced in volume, flatter in vertical dimension and non-fibrillar in comparison to control. Interestingly, single-molecule force spectroscopy data revealed that preventing disulfide bond formation weakened the non-covalent interaction forces among monomers in the aggregate by at least ten fold, thereby stalling their growth and yielding smaller aggregates in comparison to control. We conclude that while constrained protein chain dynamics in correctly disulfide bonded amyloidogenic proteins may protect them from venturing into partial folded conformations that can trigger entry into aggregation pathways, aberrant disulfide bonds in non-amyloidogenic proteins (like HEWL) on the other hand, may strengthen non-covalent intermolecular forces among monomers and promote their aggregation.

On the characterization of intermediates in the isodesmic aggregation pathway of hen lysozyme at alkaline pH.

Protein aggregation leading to formation of amyloid fibrils is a symptom of several diseases like Alzheimer's, type 2 diabetes and so on. Elucidating the poorly understood mechanism of such phenomena entails the difficult task of characterizing the species involved at each of the multiple steps in the aggregation pathway. It was previously shown by us that spontaneous aggregation of hen-eggwhite lysozyme (HEWL) at room temperature in pH 12.2 is a good model to study aggregation. Here in this paper we investigate the growth kinetics, structure, function and dynamics of multiple intermediate species populating the aggregation pathway of HEWL at pH 12.2. The different intermediates were isolated by varying the HEWL monomer concentration in the 300 nM-0.12 mM range. The intermediates were characterized using techniques like steady-state and nanosecond time-resolved fluorescence, atomic force microscopy and dynamic light scattering. Growth kinetics of non-fibrillar HEWL aggregates were fitted to the von Bertalanffy equation to yield a HEWL concentration independent rate constant (k = (6.6 ± 0.6) × 10(-5) s(-1)). Our results reveal stepwise changes in size, molecular packing and enzymatic activity among growing HEWL aggregates consistent with an isodesmic aggregation model. Formation of disulphide bonds that crosslink the monomers in the aggregate appear as a unique feature of this aggregation. AFM images of multiple amyloid fibrils emanating radially from amorphous aggregates directly confirmed that on-pathway fibril formation was feasible under isodesmic polymerization. The isolated HEWL aggregates are revealed as polycationic protein nanoparticles that are robust at neutral pH with ability to take up non-polar molecules like ANS.

Efficient dendrimer-DNA complexation and gene delivery vector properties of nitrogen-core poly(propyl ether imine) dendrimer in mammalian cells.

Dendrimers as vectors for gene delivery were established, primarily by utilizing few prominent dendrimer types so far. We report herein studies of DNA complexation efficacies and gene delivery vector properties of a nitrogen-core poly(propyl ether imine) (PETIM) dendrimer, constituted with 22 tertiary amine internal branches and 24 primary amines at the periphery. The interaction of the dendrimer with pEGFPDNA was evaluated through UV-vis, circular dichroism (CD) spectral studies, ethidium bromide fluorescence emission quenching, thermal melting, and gel retardation assays, from which most changes to DNA structure during complexation was found to occur at a weight ratio of dendrimer:DNA ∼ 2:1. The zeta potential measurements further confirmed this stoichiometry at electroneutrality. The structure of a DNA oligomer upon dendrimer complexation was simulated through molecular modeling and the simulation showed that the dendrimer enfolded DNA oligomer along both major and minor grooves, without causing DNA deformation, in 1:1 and 2:1 dendrimer-to-DNA complexes. Atomic force microscopy (AFM) studies on dendrimer-pEGFP DNA complex showed an increase in the average z-height as a result of dendrimers decorating the DNA, without causing a distortion of the DNA structure. Cytotoxicity studies involving five different mammalian cell lines, using [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide] (MTT) assay, reveal the dendrimer toxicity profile (IC50) values of ∼400-1000 µg mL(-1), depending on the cell line tested. Quantitative estimation, using luciferase assay, showed that the gene transfection was at least 100 times higher when compared to poly(ethylene imine) branched polymer, having similar number of cationic sites as the dendrimer. The present study establishes the physicochemical behavior of new nitrogen-core PETIM dendrimer-DNA complexes, their lower toxicities, and efficient gene delivery vector properties.

Lysozyme: a model protein for amyloid research.

Ever since lysozyme was discovered by Fleming in 1922, this protein has emerged as a model for investigations on protein structure and function. Over the years, several high-resolution structures have yielded a wealth of structural data on this protein. Extensive studies on folding of lysozyme have shown how different regions of this protein dynamically interact with one another. Data is also available from numerous biotechnological studies wherein lysozyme has been employed as a model protein for recovering active recombinant protein from inclusion bodies using small molecules like l-arginine. A variety of conditions have been developed in vitro to induce fibrillation in hen lysozyme. They include (a) acidic pH at elevated temperature, (b) concentrated solutions of ethanol, (c) moderate concentrations of guanidinium hydrochloride at moderate temperature, and (d) alkaline pH at room temperature. This review aims to bring together similarities and differences in aggregation mechanisms, morphology of aggregates, and related issues that arise using the different conditions mentioned above to improve our understanding. The alkaline pH condition (pH 12.2), discovered and studied extensively in our lab, shall receive special attention. More than a decade ago, it was revealed that mutations in human lysozyme can cause accumulation of large quantities of amyloid in liver, kidney, and other regions of gastrointestinal tract. Understanding the mechanism of lysozyme aggregation will probably have therapeutic implications for the treatment of systemic nonneuropathic amyloidosis. Numerous studies have begun to focus attention on inhibition of lysozyme aggregation using antibody or small molecules. The enzymatic activity of lysozyme presents a convenient handle to quantify the native population of lysozyme in a sample where aggregation has been inhibited. The rich information available on lysozyme coupled with the multiple conditions that have been successful in inducing/inhibiting its aggregation in vitro makes lysozyme an ideal model protein to investigate amyloidogenesis.

Suppression of lysozyme aggregation at alkaline pH by tri-N-acetylchitotriose.

Inhibiting protein misfolding and aggregation is imperative for treatment of amyloid diseases. In this regard small molecules which bind to and stabilize the monomeric protein have invited attention owing to their ability to significantly slow down or inhibit aggregation and amyloid formation. We have earlier shown that hen egg-white lysozyme (HEWL) spontaneously forms soluble oligomers at pH 12.2, which are later stabilized by intermolecular disulphide bonds, eventually resulting in amyloid fibrils. In this work, we show that overnight ( approximately 12 h) pre-incubation of HEWL with its competitive inhibitor, N,N',N''-Triacetylchitotriose (chitotriose) at neutral pH, impairs its aggregation and fibrillogenesis at pH 12.2. Unlike in control or N-Acetyl-D-glucosamine (NAG) pre-incubated samples, HEWL-chitotriose complex displayed i) reduced thioflavin T and ANS fluorescence, ii) small oligomers but no amyloid fibrils in AFM, iii) absence of large aggregates in SDS-PAGE and gel-filtration elutions, iv) marginally more helical content in CD spectra and v) >70% enzymatic activity after 24 h and approximately 16% activity after week long incubation at alkaline pH. It is likely that strong binding in the HEWL-chitotriose complex, in contrast to weakly bound HEWL-NAG complex, raises the activation energy barrier for protein misfolding and subsequent aggregation, thereby retarding the aggregation kinetics substantially. These results hold promise for the therapy of human lysozyme amyloidosis.

How do surfactants and DTT affect the size, dynamics, activity and growth of soluble lysozyme aggregates?

The early intermediates in the protein aggregation pathway, the elusive soluble aggregates, play a pivotal role in growth and maturation of ordered aggregates such as amyloid fibrils. Blocking the growth of soluble oligomers is an effective strategy to inhibit aggregation. To decipher the molecular mechanisms and develop better strategies to arrest aggregation, it is imperative to understand how the size, molecular dynamics, activity and growth kinetics of soluble aggregates are affected when aggregation is inhibited. With this objective, in the present study we have investigated the influence of additives such as SDS, CTAB (cetyltrimethylammonium bromide) and DTT (dithiothreitol) on the slow aggregation of HEWL (hen eggwhite lysozyme) at pH 12.2. For this purpose, techniques such as steady-state and time-resolved fluorescence anisotropy of covalently labelled dansyl probe, gel-filtration chromatography, estimation of free thiol groups, thioflavin T and ANS (8-anilinonaphthalene-1-sulfonic acid) fluorescence, CD and atomic-force microscopy were employed to monitor the soluble oligomers over a period spanning 30 days. The results of the present study reveal that: (i) the spontaneous formation of soluble aggregates is irreversible and abolishes activity; (ii) the initial growth of aggregates (0-24 h) is promoted by a gradual increase in the exposure of hydrophobic surfaces; (iii) subsequently intermolecular disulfide bonds are critical for the assembly and stability of aggregates; (iv) the tight molecular packing inside large aggregates which contributed to slow (approximately 5 ns) and restricted segmental motion of dansyl probe was clearly loosened up in the presence of additives, enabling fast (1-2 ns) and free motion (unlike DTT, the size of lysozyme complexes with surfactants, was large, due to a conglomeration of proteins and surfactants); (v) the aggregates show reduced helical content compared with native lysozyme, except in the presence of SDS; and (vi) DTT was more potent than SDS/CTAB in arresting the growth of aggregates.