FDA-Approved Chimeric Antigen Receptor (CAR)-T Cell Therapy for Different Cancers-A Recent Perspective

Cancer is one of the most prevalent diseases in the world, and their rate of occurence has been increased in recent decades. Current review article, summarizes the novel treatment options Chimeric Antigen Receptor-T (CAR-T) cell therapy for various cancers constitute a major health and development challenge, impacting every aspect of sustainable development quoted by goal 3 good health and well-being of UN sustainable goals. WHO estimates that 70% of cancer deaths occur in low- and middle- income countries (LMICs) by 2030, LMICs are expected to bear the brunt of the expected 24.1 million new cancer cases per year. This current review article focuses and discussed about CAR-T cell therapy for various cancers against most prevalent non-communicable disease cancer disease stipulated by WHO and UN sustainable goals. Three literature databases Google scholar, Science Direct, PubMed was utilized to search and collect CAR-T cell treatment options for different cancers published articles sources in between January 2000 and December 2023. There were a total of 18,700 papers found, with 48 of them being found to be eligible focusing various cancer treatment by CAR-T cells utilized for the study. Based on the information gathered, CAR-T cell therapy treating different cancers and their merit and its advantages in heal and improve certain cancers was also discussed in this review article with their detailed molecular mechanisms. This article also gives an insight to utilize CAR-T cell treatment protocols for rejuvenating cancer patient from such ruthless cancer disease condition thereby improving life span of cancer patients and eradication of disease in some cases.

AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions

Background and objective

In recent years, Artificial Intelligence has had an evident impact on the way research addresses challenges in different domains. It has proven to be a huge asset, especially in the medical field, allowing for time-efficient and reliable solutions. This research aims to spotlight the impact of deep learning and machine learning models in the detection of COVID-19 from medical images. This is achieved by conducting a review of the state-of-the-art approaches proposed by the recent works in this field.

Methods

The main focus of this study is the recent developments of classification and segmentation approaches to image-based COVID-19 detection. The study reviews 140 research papers published in different academic research databases. These papers have been screened and filtered based on specified criteria, to acquire insights prudent to image-based COVID-19 detection.

Results

The methods discussed in this review include different types of imaging modality, predominantly X-rays and CT scans. These modalities are used for classification and segmentation tasks as well. This review seeks to categorize and discuss the different deep learning and machine learning architectures employed for these tasks, based on the imaging modality utilized. It also hints at other possible deep learning and machine learning architectures that can be proposed for better results towards COVID-19 detection. Along with that, a detailed overview of the emerging trends and breakthroughs in Artificial Intelligence-based COVID-19 detection has been discussed as well.

Conclusion

This work concludes by stipulating the technical and non-technical challenges faced by researchers and illustrates the advantages of image-based COVID-19 detection with Artificial Intelligence techniques.

CT-based severity assessment for COVID-19 using weakly supervised non-local CNN

Evaluating patient criticality is the foremost step in administering appropriate COVID-19 treatment protocols. Learning an Artificial Intelligence (AI) model from clinical data for automatic risk-stratification enables accelerated response to patients displaying critical indicators. Chest CT manifestations including ground-glass opacities and consolidations are a reliable indicator for prognostic studies and show variability with patient condition. To this end, we propose a novel attention framework to estimate COVID-19 severity as a regression score from a weakly annotated CT scan dataset. It takes a non-locality approach that correlates features across different parts and spatial scales of the 3D scan. An explicit guidance mechanism from limited infection labeling drives attention refinement and feature modulation. The resulting encoded representation is further enriched through cross-channel attention. The attention model also infuses global contextual awareness into the deep voxel features by querying the base CT scan to mine relevant features. Consequently, it learns to effectively localize its focus region and chisel out the infection precisely. Experimental validation on the MosMed dataset shows that the proposed architecture has significant potential in augmenting existing methods as it achieved a 0.84 R-squared score and 0.133 mean absolute difference.

Ischemic Lesion Segmentation using Ensemble of Multi-Scale Region Aligned CNN

The first and foremost step in the diagnosis of ischemic stroke is the delineation of the lesion from radiological images for effective treatment planning. Manual delineation of the lesion by radiological experts is generally laborious and time-consuming. Sometimes, it is prone to intra-observer and inter-observer variability. State of the art deep architectures based on Fully Convolutional Networks (FCN) and cascaded CNNs have shown good results in automated lesion segmentation. This work proposes a series of enhancements over the learning paradigm in the existing methods, by focusing on learning meticulous feature representations through the CNN layers for accurate ischemic lesion segmentation from multimodal MRI. Multiple levels of losses, integration of features from multiple scales, an ensemble of prediction maps from sub-networks are employed to enable the CNN to correlate between features seen from different receptive fields. To allow for progressive refinement of features from block to block, a custom dropout module has been proposed that suppresses noisy features. Multi-branch residual connections and attention mechanisms were also included in the CNN blocks to enable the integration of information from multiple receptive fields and selectively weigh significant features. Also, to tackle data imbalance both at voxel and sample level, patch-based modeling and separation of concerns into classification & segmentation functional branches are proposed. By incorporating the above mentioned architectural enhancements, the proposed deep architecture was able to achieve better segmentation performance against the existing models. The proposed approach was evaluated on the ISLES 2015 SISS dataset, and it achieved a mean dice coefficient of 0.775. By combining sample classification and lesion segmentation into a fully automated framework, the proposed approach has yielded better results compared to most of the existing works.

Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification

BACKGROUND AND OBJECTIVE

Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals.

METHODS

Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well.

RESULTS

Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%.

CONCLUSION

The experimental results indicated that the proposed combination of feature extraction and selection method offers suitable classification accuracy and may be employed to detect the subtle changes in the cry signals.

Locality sensitivity discriminant analysis-based feature ranking of human emotion actions recognition

[Purpose] Computational intelligence similar to pattern recognition is frequently confronted with high-dimensional data. Therefore, the reduction of the dimensionality is critical to make the manifold features amenable. Procedures that are analytically or computationally manageable in smaller amounts of data and low-dimensional space can become important to produce a better classification performance. [Methods] Thus, we proposed two stage reduction techniques. Feature selection-based ranking using information gain (IG) and Chi-square (Chisq) are used to identify the best ranking of the features selected for emotion classification in different actions including knocking, throwing, and lifting. Then, feature reduction-based locality sensitivity discriminant analysis (LSDA) and principal component analysis (PCA) are used to transform the selected feature to low-dimensional space. Two-stage feature selection-reduction methods such as IG-PCA, IG-LSDA, Chisq-PCA, and Chisq-LSDA are proposed. [Results] The result confirms that applying feature ranking combined with a dimensional-reduction method increases the performance of the classifiers. [Conclusion] The dimension reduction was performed using LSDA by denoting the features of the highest importance determined using IG and Chisq to not only improve the effectiveness but also reduce the computational time.

Congenital nasal pyriform aperture stenosis: a rare cause of neonatal nasal airway obstruction

Congenital nasal pyriform aperture stenosis (CNPAS) is a rare cause of nasal airway obstruction that clinically mimics choanal atresia in a neonate. The differentiation between the two is very important as the management of the two conditions is different. Timely recognition is important to prevent fatal outcome. CNPAS may present as an isolated condition or with associated craniofacial anomalies. Despite typical findings of CNPAS being present on cross-sectional imaging, this condition is commonly overlooked, probably because of a lack of familiarity with the normal morphological features of the nasal cavity in infants and also owing to a lack of awareness of this rare entity. Here we report a case of CNPAS with pre- and post-surgical CT images and the complication that occurred owing to nasal stenting.

A new hybrid intelligent system for accurate detection of Parkinson's disease

Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset.

Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network

Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and it has been proven to be an excellent tool to investigate the pathological status of an infant. This paper proposes short-time Fourier transform (STFT) based time-frequency analysis of infant cry signals. Few statistical features are derived from the time-frequency plot of infant cry signals and used as features to quantify infant cry signals. General Regression Neural Network (GRNN) is employed as a classifier for discriminating infant cry signals. Two classes of infant cry signals are considered such as normal cry signals and pathological cry signals from deaf infants. To prove the reliability of the proposed features, two neural network models such as Multilayer Perceptron (MLP) and Time-Delay Neural Network (TDNN) trained by scaled conjugate gradient algorithm are also used as classifiers. The experimental results show that the GRNN classifier gives very promising classification accuracy compared to MLP and TDNN and the proposed method can effectively classify normal and pathological infant cries.

Solvent, emulsifier and drug concentration factors in poly(D,L-lactic acid) microspheres containing hexamethylmelamine

Biodegradable poly(D,L-lactic acid) (PLA) microspheres containing hexamethylmelamine (HMM) were developed for potential use in chemoembolization and intraperitoneal implantation. The emulsion-solvent-evaporation/extraction method was used to prepare 15 formulations with different drug/polymer ratios, solvent compositions and emulsifer concentrations in the continuous aqueous phase. A central composite experimental design was used, with five levels of the three different factors. All formulations resulted in the formation of discrete matrix microspheres containing crystalline drug. The mean particle sizes of the microsphere formulations ranged from 62-348 microm and the effect of the independent variables on microsphere size was satisfactorily predicted using response surface methodology. For theoretical drug loads of 5-40%, efficiency of entrapment ranged from 75-107% and porosities of the microspheres were between 0-6.5%. The rate of drug release from the microspheres depended on drug loading and particle size. Microspheres with 22.5% or greater theoretical drug content released drug rapidly, with almost complete release occurring in 70 h or less. Formulations with drug loading of 5% and 9.57%, however, released drug very slowly, with less than 50% released in 40 days. Release kinetics of narrow sieve cuts of microspheres with high drug load (35.4%) followed square root of time profiles.

Controlled-release tablets from carrageenans: effect of formulation, storage and dissolution factors

The purpose of this study was to investigate the potential of two carrageenans, iota-carrageenan and lambda-carrageenan for the preparation of controlled-release tablets. Tablets were compressed on a Carver press and the effect of formulation factors, moisture, and storage on the release of theophylline was studied. The effect of sodium chloride in the tablet formulation and a change in the ionic strength of the dissolution media was studied on the release of three model drugs. The release rate increased both with an increase in tablet diameter and increase in drug to carrageenan ratio in the tablets. The two lubricants studied had a negligible effect on the rate of drug release at their commonly used concentrations. Moisture content of carrageenans, storage of tablets at 37 degrees C/75% RH for 3 months, and incorporation of 10% sodium chloride in the tablets did not have any significant effect on the release rate. The change in ionic strength of simulated gastric fluid altered the release rate whereas the ionic strength of simulated intestinal fluid did not have a significant effect on the release rate. Carrageenan tablets were relatively insensitive to small changes in formulation parameters and dissolution conditions.

Sustained high-level expression of full-length human factor VIII and restoration of clotting activity in hemophilic mice using a minimal adenovirus vector

The successful prophylactic treatment of hemophilia A by frequent infusions of plasma concentrates or recombinant factor VIII (hFVIII) indicates that gene therapy may be a potential alternative for the treatment of the disease. For efficient delivery and long-term expression of the hFVIII gene, a novel minimal adenovirus (mini-Ad) vector, MiniAdFVIII, has been developed. The vector is devoid of all viral genes and carries the full-length hFVIII cDNA under the control of the human 12.5-kb albumin promoter. The MiniAdFVIII vector was propagated with the assistance of an ancillary vector in 293 cells and was purified by CsCl banding. Sustained expression of hFVIII at physiologic levels (100-800 ng/mL) was achieved in mice after a single intravenous injection of MiniAdFVIII. The expressed hFVIII had a structure identical to that of recombinant hFVIII, as determined by Western blot analysis. The functionality of the protein was confirmed by the restoration of blood coagulation capacity in MiniAdFVIII-treated hemophilic mice, as determined by tail clipping observations. Although antivector or antihuman FVIII antibodies at various levels were detected, long-term expression of the transgene was observed in the mice that did not generate antibodies against the transgene product. The vector DNA persisted in the liver tissues of the mice with long-term expression. No significant histopathologic findings or toxicities were observed to be associated with the vector in the MiniAdFVIII-treated C57BL/6 mice. These results support the further development of MiniAdFVIII for clinical trials toward the treatment of hemophilia A.

A case-control study on risk factors for pancreatic diseases in Kerala, India

BACKGROUND/AIMS

We simultaneously conducted case-control studies, in Kerala of South India, on chronic calcific pancreatitis of the tropics (CCPT), pancreatic ductal adenocarcinoma (PDA) with CCPT, and PDA alone to assess similarity of and difference between their risk factors.

METHODOLOGY

Cases with one of these diseases were identified at the Trivandrum Medical College (TMC) Hospital, in Kerala, from 1994 to 1996. Controls were selected from healthy hospital visitors of the TMC Hospital by individual age (within +/- 3 years) and sex-matched with the index case. Odds ratios and their 95% confidence intervals for potential risk factors were calculated.

RESULTS

Frequent consumption of cassava was positively associated with the risk of PDA with CCPT. Heavy cigarette smoking and drinking large amounts of coffee and/or tea everyday were positively related to the risk of PDA alone. Frequent consumption of vegetables and/or fruits was correlated to the decreased risk of PDA alone.

CONCLUSIONS

Risk factors as well as preventive factors seem to be different between PDA with CCPT and PDA alone. Further study is necessary, especially to clarify the prognostic factors which would induce pancreatic malignancy in patients with CCPT.

Plasmid DNA-based alphavirus expression vectors for nucleic acid immunization

Alphavirus-derived vectors are being developed for vaccine, gene therapy and recombinant protein production applications, based in part on observations of transient, high level expression of heterologous genes in eukaryotic cells. Efficient means for launching the RNA alphavirus genome from RNA polymerase II expression cassettes have been developed, obviating the need for transcription in vitro of long cDNA templates. One system being developed from this technology is a layered plasmid DNA vector which, when inoculated directly into animal muscle, launches a self-amplifying alphavirus vector, resulting in subsequent induction of comparatively robust immune responses specific for the expressed antigen.

Effects of the T-->R transition on the electrostatic properties of E. coli aspartate transcarbamylase

Aspartate transcarbamylase is a large (310 kD), multisubunit protein that binds substrates cooperatively and undergoes a large change in quaternary structure when substrates bind. The forces that drive this transition are poorly understood. We evaluated the electrostatic component of these forces by using finite difference and multigrid methods to solve the nonlinear Poisson-Boltzmann equation for complexes of the enzyme with several substrates and substrate analogs. The results have been compared with calculations for the unliganded protein. While pK1/2 values of most ionizable residues fall within 3 pH units of values for model compounds, 31 have pK1/2 values that fall outside the range 0-17. Many of these residues are at the active site, where they interact with the highly charged substrate, in the 80s loop or 240s loop or interact with these loops. The pK1/2 values of eight ionizable residues related by the twofold molecular axes differ by more than 3 pH units, providing additional evidence for asymmetry within the crystal. As in the unliganded structure, a set of residues forms a network in which ionizable groups with Wij values greater than 2 kcal-m(-1) are separated by distances greater than 5 A. Some residues participate in this network in both the unliganded and N-phosphonacetyl-L-aspartate (PALA)-liganded structure, while others are found in only one structure. The network is more extensive in the PALA-liganded structure than in the unliganded structure, but consists of two separate networks in the two halves of the molecule.

Ionic properties of membrane association by vitamin K-dependent proteins: the case for univalency

Ionic properties of membrane interaction by prothrombin, protein Z, and other vitamin K-dependent proteins were studied to determine the relevance of a monovalent membrane contact mechanism between one phospholipid headgroup and a calcium-lined pore in the protein [McDonald, J. F., Shah, A. M., Schwalbe, R. A., Kisiel, W., Dahlback, B., and Nelsestuen, G. L. (1997) Biochemistry 36, 5120-5127]. For comparison, multivalent ionic interaction was illustrated by peptides of +3 to +5 net charge and by blood clotting factor V. As expected, the peptides were easily dissociated by salt and gave nominal charge-charge interactions (zazb values) of -13 to -17. Factor V showed much higher binding affinity despite nominal zazb values of about 9. Membrane-bound prothrombin and protein Z showed very low sensitivity to salt as long as calcium was at saturating levels (zazb values of approximately -1.3 to -1.4), appropriate for univalent ionic attraction. Prothrombin contains +3 charge groups (Lys-2, Lys-11, Arg-10) that are absent from the GLA domain (residues 1-35) of protein Z, while protein Z contains -4 charge groups (Gla-11, Asp-34, Asp-35) that are absent in prothrombin. Thus, similar zazb relationships indicated little role for these surface charges in direct membrane contact. Calcium-saturated protein Z bound to phosphatidylcholine (PC) in a manner which indicated the addition of one calcium ion, bringing the total calcium stoichiometry in the protein-membrane complex to at least 8. Protein Z bound to phosphatidic acid (PA) in a manner suggesting the need for a fully ionized phosphate headgroup, a property expected by ion pairing in an isolated environment. Electrostatic calculations showed that the proposed protein site for phosphate interaction was electropositive. The cluster of hydrophobic amino acids (Phe-5, Leu-6, and Val-9) on the surface of prothrombin was electronegative, suggesting a role in the electrostatic architecture of the GLA domain. Overall, membrane binding by vitamin K-dependent proteins appeared consistent with the formation of an ion pair in an isolated environment.

Controlled-release tablet matrices from carrageenans: compression and dissolution studies

This study investigates the potential of two commercial carrageenans, Gelcarin GP-379 (iota-carrageenan) and Viscarin GP-209 (lambda-carrageenan) to be used for the preparation of controlled-release tablet matrices. Tablets were compressed on an instrumented Stokes single punch machine and compression characteristics of the carrageenans were analyzed. Heckel plots using out-of-die tablet densities were linear with calculated yield pressures of 81.3 MPa and 105.2 MPa for iota- and lambda-carrageenan, respectively. Drug release from tablet formulations that contained equal amounts of the two carrageenans had near zero-order release profiles. There was little or no effect of tablet compression pressure on the drug release profiles from 70 to 175 MPa. As drug loading was increased from 5 to 20%, the diffusional exponent decreased from 1.056 to 0.678. Thirty percent drug loading resulted in breakup of tablets during dissolution and departure from zero-order release. Multiple regression analysis was used to predict the time for 50% release as a function of the concentration of the two carrageenans and a third filler material, microcrystalline cellulose. Predicted values were in good agreement with observed values and R2 for the final cubic model was 0.9984.

Optimization of sustained-release tablet formulations: a four-component mixture experiment

Sustained-release tablet formulations containing chlorpheniramine maleate were prepared using a mixture of two hydrophilic gums, gamma-carrageenan and cross-linked carboxymethylcellulose sodium, and two filler materials, alpha-lactose monohydrate and dibasic calcium phosphate in different ratios. The objective of the experiment was to find an optimum formulation with the most desirable properties. In order to achieve this, the matrices were evaluated for the time taken to release 80% drug (t80), the release exponent (n), and the crushing strength (h). Several formulations produced near zero-order release of the model drug over a time period of up to 10 hr. Response surface plots for the three dependent variables were generated over the experimental region. the effect of different levels of the components on the response variables was thus visualized. Upon superimposition of the plots it was possible to graphically find a region where the responses were in an optimum range of values. To pinpoint the best formulation, a simultaneous optimum point within this region was located by arbitrarily defining optimum values for each of the responses and using a multi-objective function that combined the three response variables. The observed response variables of the optimum formulation were in good agreement with the predicted values.

Cognitive, behavioral, and motor effects of the NMDA antagonist ketamine in Huntington's disease

BACKGROUND

Excitotoxicity may contribute to neuronal degeneration in Huntington's disease (HD). N-methyl-D-aspartate (NMDA) receptor antagonists can prevent neuronal degeneration caused by excitotoxicity, but their effects in HD patients are not known.

METHODS

We investigated the acute cognitive, behavioral, and motor effects of the NMDA-receptor antagonist ketamine in HD patients. Double-blind infusions of 0.10, 0.40, and 0.60 mg/kg/hr ketamine were given to 10 HD patients on one test day and compared with placebo infusions on a second, identical testing day. Linear mixed-effects models and randomization tests were used to identify whether, and at which dose, a significant change from baseline occurred in outcome variables.

RESULTS

We demonstrated that ketamine is well tolerated at low and intermediate subanesthetic doses. Intermediate ketamine doses produced specific decline in memory and verbal fluency. Higher subanesthetic doses caused a significant increase in psychiatric symptoms and impairment of eye movements.

CONCLUSIONS

These results describe the spectrum of clinical effects produced by increasing NMDA receptor blockade in HD patients. The clinical effects appearing with higher levels of NMDA receptor blockade can identify the range of doses used in clinical trials of NMDA receptor antagonists.

The effect of paroxetine on thiothixene pharmacokinetics

OBJECTIVE

In this study healthy volunteers received thiothixene with and without a 3-day pretreatment with paroxetine to determine if paroxetine decreased the clearance of thiothixene.

METHOD

Ten healthy medication-free volunteers (4 women and 6 men, mean age 38 +/- 12 years) were randomized to receive a single 20 mg oral dose of thiothixene on two separate occasions. On one occasion thiothixene was given concurrently, and following 3 days of pre-treatment with oral paroxetine (20 mg/day). On the other occasion thiothixene was given without paroxetine pre-treatment. The two study days were separated by a minimum period of 2 weeks. On both study days, after the administration of thiothixene, 10 ml blood samples were collected over the next 72 h.

RESULTS

None of the pharmacokinetic parameters of thiothixene were significantly altered by a 3-day treatment with paroxetine.

DISCUSSION

It is likely that the CYP2D6 isoenzyme is not responsible for a high proportion of thiothixene clearance, but one cannot exclude the possibility that a longer paroxetine pretreatment might have caused some inhibition of thiothixene clearance.

Consensus chemistry and beta-turn conformation of the active core of the insect kinin neuropeptide family

BACKGROUND

Neuropeptides are examples of small, flexible molecules that bind to receptors and induce signal transduction, thereby eliciting biological activity. The multifunctional insect kinin neuropeptides retain full activity when reduced to only their carboxy-terminal pentapeptide (Phe1-X2-X3-Trp4-Gly5-NH2), thereby allowing extensive structure-function studies and conformational analysis.

RESULTS

A combined experimental and theoretical analysis of the insect kinin carboxy-terminal pentapeptide was used to probe the role of each residue, define the bioactive conformation, and design a constrained bioactive analog. Coupling receptor-binding data with two biological activity assays allowed receptor binding and signal transduction to be differentiated. A preferred beta-turn conformation, found for residues 1-4 by molecular dynamics simulations, was tested by designing a conformationally restricted cyclic hexapeptide. This cyclic analog showed a preference for the beta-turn conformation, as shown by a conformational search and nuclear magnetic resonance spectroscopy, and it showed stronger receptor binding but decreased activity relative to highly active linear analogs.

CONCLUSIONS

Each residue of the insect kinin carboxy-terminal pentapeptide has a distinct role in conformational preference, specific receptor interactions or signal transduction. The beta-turn preference of residues Phe1-X2-X3-Trp4 implicates this as the bioactive conformation. The amidated carboxyl terminus, required for activity in many neuropeptide families, may be generally important for signal transduction and its inclusion may therefore be essential for agonist design.

Platelet alpha 2-adrenoreceptors, catecholamines, hemodynamic variables, and anxiety in panic patients and their asymptomatic relatives

The objectives of this study were to a) replicate our prior finding of a decreased number (Bmax) of platelet alpha 2-adrenoreceptors in panic disorder, b) determine if binding is also decreased in asymptomatic first-degree relatives of panic patients (known to be at increased risk for developing panic), and c) evaluate the effect of treatment on the presumptive decrease in binding (i.e., is the decrease a state or a trait marker for panic?). Panic patients had clonidine and yohimbine platelet-binding assays, symptom ratings, and measurement of lying and standing plasma epinephrine, norepinephrine, systolic and diastolic blood pressure, and heart rate before treatment, after approximately 2 months of medication (fluoxetine, tricyclics, or alprazolam) and/or cognitive behavioral treatment, and after symptom remission while drug free; normal subjects had determinations of the same measures at approximately the same time intervals. Relatives of both groups had one determination only of all measures. Tritiated clonidine binding was decreased and lying heart rate was increased in patients before treatment. Magnitude of binding decrease was correlated with symptom severity and standing norepinephrine. No binding abnormality was seen in first-degree relatives of patients. Treatment increased clonidine binding in patients. Both patients and relatives of patients showed significantly increased standing plasma norepinephrine in comparison to controls. There is a state-related decrease in binding, associated with symptom severity and norepinephrine, in panic disorder. Abnormal reactivity of norepinephrine to standing might be a marker for increased likelihood of panic development in individuals at risk.

Molecular structure, conformational analysis, and structure-activity studies of Dendrotoxin and its homologues using molecular mechanics and molecular dynamics techniques

Three-dimensional structures of Dendrotoxin (DtX), Toxin-I (DpI), and Toxin-K (DpK) were determined using molecular mechanics and molecular dynamics techniques. The overall molecular conformation and protein folding of the three dendrotoxins are very similar to the published crystal structures of bovine pancreatic trypsin inhibitor (BPTI) and alpha-DtX. Major secondary structural regions of the dendrotoxins are stable without much fluctuation during the dynamics simulation; the regions corresponding to the turns and bends (rich in lysines and arginines) exhibit more fluctuations. The conformational angles and the C alpha...C alpha' distances of the three disulfides (in each of the dendrotoxins) are different from each other. Comparative model building studies, involving the dendrotoxins and the proteinases, reveal that the key interactions (observed in BPTI-trypsin complex) needed for anti-protease activity are absent due to structural differences between the dendrotoxins and BPTI at the anti-protease loop; this explains the inability of the dendrotoxins to inhibit proteinases. The model also suggests that the solvent-exposed beta-turn region, rich in lysines (residues 26-28), might bind directly to the extracellular anionic sites of the receptors (K+ channels) by ionic interactions. The strikingly homologous cysteine distribution (Cys-x-x-x-Cys) in DtX, DpI, and DpK, at the C-terminus, induces the occurrence of a characteristic conformational motif, consisting of an alpha-helix (in an amphiphilic environment) stabilized by two disulfides, one involving a cysteine at the beta-strand, and the other at the N-terminus. This amphiphilic secondary structural element seems to provide the rigid frame work needed for exposing the proposed active site region of the dendrotoxins to the anionic sites of the K+ channel receptors.

The role of melatonin in the pathogenesis of adolescent idiopathic scoliosis

STUDY DESIGN

A matched, case-control study comparing melatonin production in female patients with and without adolescent idiopathic scoliosis.

OBJECTIVES

To determine whether melatonin production is decreased in adolescent idiopathic scoliosis.

SUMMARY OF BACKGROUND DATA

A central etiology for idiopathic scoliosis has never been established. Previous authors have produced experimental scoliosis in chickens after pinealectomy, preventable by administration of melatonin. They suggested that a defect in melatonin synthesis might be involved in the pathogenesis of human idiopathic scoliosis.

METHODS

Nine female adolescents with no medical problems, normal neurologic examinations, radiographic idiopathic scoliosis of 15-40 degrees, and Risser Stage I-III were in the patient group. Eighteen healthy adolescent girls with no medical problems, a negative school screening, and no family history of scoliosis were control subjects. Patients and control subjects were matched for age, weight, Tanner stage, sleep duration, and light exposure by multiple linear regression. Nighttime and daytime urine samples were analyzed for melatonin by high-performance liquid chromatography.

RESULTS

Although nighttime melatonin levels were significantly higher than daytime levels in all volunteers (P < 0.00002), there were no significant differences in nighttime (P > 0.63) or daytime (P > 0.78) melatonin levels between patients and control subjects, even after matching by multiple linear regression analysis. A statistical analysis demonstrated that if a melatonin deficiency of 25% or more did exist in patients with scoliosis compared with control subjects, the likelihood that it would have been detected in this study was more than 98%.

CONCLUSION

Although melatonin deficiency may cause scoliosis in the chicken, this study suggests that it is not a mechanism in the pathogenesis of adolescent idiopathic scoliosis in humans.

Urinary catecholamine excretion and behavioral differences in ADHD and normal boys

Urinary catecholamine excretion was assessed in 15 boys with attention-deficit/hyperactivity disorder (ADHD) and 16 normal controls during a defined physical and mental task. Dihydroxyphenylalanine, dopamine, norepinephrine (NE), epinephrine (EPI), 3,4-dihydroxyphenylacetic acid, and 3,4-dihydroxyphenylglycol (DOPEG) concentrations were assayed by high-pressure liquid chromatography with electrochemical detection. The urinary concentration of DOPEG, an NE metabolite that has not been previously measured in ADHD, was significantly lower in the ADHD subjects than in the normal controls. There was also a trend for lower urinary EPI levels in the hyperactive boys. Stepwise multiple regression analyses demonstrated that DOPEG and EPI each contributed significantly to the variance in the behavioral symptoms within the full sample. The results are consistent with previous reports of abnormal metabolism of norepinephrine and epinephrine in ADHD. These neurochemical findings may be due to differences between ADHD and normal boys in neuronal (central or peripheral) or nonneuronal (e.g., adrenal, renal) activity. The results are also consistent with prior findings in normal children of an inverse relationship between EPI excretion and inattentive, restless behaviors. Together, these findings suggest caution in ascribing metabolite changes to ADHD or to ADHD-like behaviors that may be seen in normal children.

Identification of a novel integrin binding site in fibronectin. Differential utilization by beta 3 integrins

Fibronectin (Fn) binding to the integrins alpha IIb beta 3 and alpha v beta 3 involves the Arg-Gly-Asp sequence. The identification of other regions of Fn that interact with alpha IIb beta 3 suggests a potential mechanism for differential ligand recognition by integrins. We report here the identification of an 11-residue peptide sequence from the 9th type III repeat of Fn (3Fn9), which inhibits ligand binding to alpha IIb beta 3 by interacting directly with this receptor. Mutational analysis demonstrated that this same region was involved in the formation of epitopes for two anti-Fn mAbs that inhibit Fn binding to alpha IIb beta 3, thus emphasizing the role of this site in the macromolecule. Molecular modeling of the 3Fn9-10 modules suggested that Fn residues Asp1373-Thr1383 are at least 25 A distant from the Arg-Gly-Asp site and therefore does not directly interact with it. The 3Fn9 site was differentially recognized by the beta 3 integrin family. The Asp1373-Thr1383 peptide failed to inhibit ligand binding to alpha v beta 3, a recombinant Fn Ala1235-Ser1436 fragment was not recognized by alpha v beta 3, and addition of the 3Fn9 module to the amino terminus of the 3Fn10 did not affect the potency of inhibition of Fn binding to alpha v beta 3. Thus, a novel integrin recognition site in the 3Fn9 module of Fn that is differentially recognized by the beta 3 integrins has been localized within the residues Asp1373-Thr1383.