Rebound Exercises in Rehabilitation: A Scoping Review.

The term "trampoline" was coined in 1969, introducing a dynamic feedback mechanism for exercise. Rebounding exercise on a mini-trampoline utilizes an elastic surface supported by springs and gravity, potentially reducing cumulative trauma from repetitive loading. This type of physical activity provides enjoyable and engaging exercise for adolescents, especially those who are overweight, thereby reducing the likelihood of injuries associated with exercise. Mini-trampoline exercises enhance blood circulation, oxygen delivery, and bone health, impacting lower limb strength, balance, motor performance, blood glucose levels, executive function, physiological markers, and overall quality of life. The study focused on examining the overall impact of rebounding exercises in the field of rehabilitation. Its main goal was to assess how these exercises affect the rehabilitation process and different health measures. By investigating the comprehensive influence of rebounding exercises, the study aimed to determine their effectiveness in aiding physical and functional recovery, targeting specific rehabilitation goals, and enhancing overall health outcomes. We systematically reviewed medical literature databases such as PubMed, MEDLINE, Scopus, Google Scholar, and EBSCO. We included research articles, systematic reviews, meta-analyses, clinical trials, case studies, and observational studies published in English up to 10 years before the review's cutoff in December 2023. We considered participants across all age groups. Articles not in English were excluded from the review. The outcome measures were body composition, waist-hip ratio, Bruininks-Oseretsky test for motor proficiency, reaction time, insulin resistance, lipid profile, blood cholesterol level, forced expiratory volume in one second, and forced vital capacity, bone health indicators, blood lactate level, balance, strength: repetitive maximum, brief pain inventory (short form). A total of 11 reports met these criteria. In conclusion, this review provides a thorough look into the use, challenges, and future potential of rebound exercises in rehabilitation and fitness. Despite their wide-ranging applications, issues such as insufficient research, equipment variability, and safety concerns persist. Advancement requires more research for evidence-based guidelines, improved equipment design and safety measures, and collaboration among researchers, clinicians, and manufacturers. Overcoming challenges and fostering innovation can establish rebound exercises as a valuable tool in rehabilitation and fitness.

Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital.

Objectives: Radiation therapy for lung cancer requires a gross tumour volume (GTV) to be carefully outlined by a skilled radiation oncologist (RO) to accurately pinpoint high radiation dose to a malignant mass while simultaneously minimizing radiation damage to adjacent normal tissues. This is manually intensive and tedious however, it is feasible to train a deep learning (DL) neural network that could assist ROs to delineate the GTV. However, DL trained on large openly accessible data sets might not perform well when applied to a superficially similar task but in a different clinical setting. In this work, we tested the performance of DL automatic lung GTV segmentation model trained on open-access Dutch data when used on Indian patients from a large public tertiary hospital, and hypothesized that generic DL performance could be improved for a specific local clinical context, by means of modest transfer-learning on a small representative local subset. Methods: X-ray computed tomography (CT) series in a public data set called "NSCLC-Radiomics" from The Cancer Imaging Archive was first used to train a DL-based lung GTV segmentation model (Model 1). Its performance was assessed using a different open access data set (Interobserver1) of Dutch subjects plus a private Indian data set from a local tertiary hospital (Test Set 2). Another Indian data set (Retrain Set 1) was used to fine-tune the former DL model using a transfer learning method. The Indian data sets were taken from CT of a hybrid scanner based in nuclear medicine, but the GTV was drawn by skilled Indian ROs. The final (after fine-tuning) model (Model 2) was then re-evaluated in "Interobserver1" and "Test Set 2." Dice similarity coefficient (DSC), precision, and recall were used as geometric segmentation performance metrics. Results: Model 1 trained exclusively on Dutch scans showed a significant fall in performance when tested on "Test Set 2." However, the DSC of Model 2 recovered by 14 percentage points when evaluated in the same test set. Precision and recall showed a similar rebound of performance after transfer learning, in spite of using a comparatively small sample size. The performance of both models, before and after the fine-tuning, did not significantly change the segmentation performance in "Interobserver1." Conclusions: A large public open-access data set was used to train a generic DL model for lung GTV segmentation, but this did not perform well initially in the Indian clinical context. Using transfer learning methods, it was feasible to efficiently and easily fine-tune the generic model using only a small number of local examples from the Indian hospital. This led to a recovery of some of the geometric segmentation performance, but the tuning did not appear to affect the performance of the model in another open-access data set. Advances in knowledge: Caution is needed when using models trained on large volumes of international data in a local clinical setting, even when that training data set is of good quality. Minor differences in scan acquisition and clinician delineation preferences may result in an apparent drop in performance. However, DL models have the advantage of being efficiently "adapted" from a generic to a locally specific context, with only a small amount of fine-tuning by means of transfer learning on a small local institutional data set.

A Simplified Risk Score to Estimate the Risk of Contrast-Induced Nephropathy after Contrast Exposure.

Introduction: Scores are available to predict the probability of contrast-induced nephropathy (CIN) after cardiac interventions, but not many scores are available for non-cardiac interventions and there are none for intravenous exposure to contrast. We designed this study to develop a simplified score to determine the probability of developing CIN in patients exposed to the parenteral contrast medium. Methods: This was a prospective study of patients who received parenteral contrast. Of 1300 patients, the first 1000 comprised the derivation cohort and the next 300 comprised the validation cohort. The patient variables in the development cohort were studied using univariate analysis. Statistically significant individual variables were used as independent variables, and CIN was used as the dependent variable in the final multivariate logistic regression model. Then, the risk score was obtained and validated. Results: The incidence of CIN was 3.8%. The risk factors, namely the presence of diabetes mellitus, e-GFR, and route and volume of contrast material were significantly associated with the risk of CIN (P < 0.05). The developed risk score had a sensitivity of 90.4% and specificity of 98.78%. The overall accuracy was 97.8%. The values of AUC of ROC in the development and validation datasets were high. This indicated that the predicted CIN risk score correlated well with the calibration and discriminative characteristics. Conclusions: The route and volume of contrast administered, low e-GFR, and diabetes mellitus were the significant risk factors. The developed risk score exhibited very good sensitivity and specificity and excellent accuracy in predicting the probability of CIN.

Scene-dependent, feedforward eye gaze metrics can differentiate technical skill levels of trainees in laparoscopic surgery.

INTRODUCTION: In laparoscopic surgery, looking in the target areas is an indicator of proficiency. However, gaze behaviors revealing feedforward control (i.e., looking ahead) and their importance have been under-investigated in surgery. This study aims to establish the sensitivity and relative importance of different scene-dependent gaze and motion metrics for estimating trainee proficiency levels in surgical skills. METHODS: Medical students performed the Fundamentals of Laparoscopic Surgery peg transfer task while recording their gaze on the monitor and tool activities inside the trainer box. Using computer vision and fixation algorithms, five scene-dependent gaze metrics and one tool speed metric were computed for 499 practice trials. Cluster analysis on the six metrics was used to group the trials into different clusters/proficiency levels, and ANOVAs were conducted to test differences between proficiency levels. A Random Forest model was trained to study metric importance at predicting proficiency levels. RESULTS: Three clusters were identified, corresponding to three proficiency levels. The correspondence between the clusters and proficiency levels was confirmed by differences between completion times (F2,488 = 38.94, p < .001). Further, ANOVAs revealed significant differences between the three levels for all six metrics. The Random Forest model predicted proficiency level with 99% out-of-bag accuracy and revealed that scene-dependent gaze metrics reflecting feedforward behaviors were more important for prediction than the ones reflecting feedback behaviors. CONCLUSION: Scene-dependent gaze metrics revealed skill levels of trainees more precisely than between experts and novices as suggested in the literature. Further, feedforward gaze metrics appeared to be more important than feedback ones at predicting proficiency.

Rehabilitation and Management of Complex Multiple Para-Symphysis Mandible Fracture: A Case Report.

Fractures of the parasymphysis occur in 15% of all cases of mandibular fracture. The mandible occupies the lowest portion of the face. The prominent bone of the face is severely injured when the lower face is hit by high impacts with upward or obliquely directed force. In this case study, we discussed the alleged trauma case of a 20-year-old man who fell from a height on August 27, 2022, at about 9:00 p.m. near Wardha. His family took him to the hospital in Wardha due to pain that was aggravated during chewing and swelling in his jaw. On investigation, an X-ray was done, and a left parasymphysis and right-side body fracture were noticed. Later, the patient underwent surgery, where open reduction and internal fixation of the left parasymphysis and the right-side body fracture with plating and intermaxillary fixation (IMF) were done. Then he was referred to the physiotherapy department for therapeutic intervention. Rehabilitation was given to reduce pain and swelling, regain full range of motion, gradually increase mobility, and keep associated muscles strong. A six-week protocol was administered to the patient. It was found that the therapeutic approach was quite effective for the patient.

Physical Therapy Management in a Severe Case of Overlapping of Bone Post Crush Injury: A Case Report.

Crush injuries are sustained due to high velocity and usually have a poor outcome. Since the compressive forces are of high energy, such injuries are usually seen in road traffic accidents or in industrial workers. Crush injuries of the hand account for relatively a smaller percentage of the injuries to the hand and include an open wound along with fracture dislocation of the carpometacarpal, interphalangeal, and radiocarpal joints. Since these injuries are uncommon, they are often overlooked in radiological findings or misdiagnosed. Their recognition depends on a careful physical and radiographic examination that may require trispiral computed tomograms. Physical therapy rehabilitation post-surgery becomes a necessity, especially in cases where the dominant hand is affected. Functional rehabilitation to improve the independence and efficiency of activities of daily living is a goal of utmost importance.

Effect of Dance Movement Therapy on Cancer-Related Fatigue in Breast Cancer Patients Undergoing Radiation Therapy: A Pre-post Intervention Study.

Introduction Dance movement therapy (DMT) is a movement-based psychosocial intervention that incorporates the therapeutic components of dance movements and group psychotherapy. DMT, also known as creative movement therapy (CMT) is a psychotherapy used as a complementary therapy in cancer care. It helps in enhancing mood, emotions, self-expression and helps to rebuild self-confidence. Besides, it allows the patients to recognise their own strengths and weaknesses as well as helps to improve physical capabilities. Methods By simple random sampling method, 30 breast cancer patients were recruited at Pravara Rural Hospital, Loni, Maharashtra, India. The participants were in the age range of 30-60 years based on the inclusion and exclusion criteria. Pre-intervention scores of cancer-related fatigue (CRF) were taken using the Brief Fatigue Inventory (BFI) scale and intervention was given for 45 minutes each day for 5 days a week, over a span of 2 weeks. Thereafter, post-intervention assessment was done and the scores were noted. Pre-intervention and post-intervention scores were compared using paired t-test. Results The mean and standard deviation (SD) of pre- and post-BFI scores derived by using paired t-test was 73.76 (8.6) and 69.33 (9.8), respectively, with a p-value of < 0.001, which is highly significant. Conclusion The results of the present study revealed that DMT seems to be effective in reducing some amount of CRF in breast cancer patients undergoing radiation therapy. Besides, it turned out to be an engaging, entertaining and cost-effective approach. The investigation showed that DMT appears to be beneficial in reducing the side effects of radiation therapy such as pain, stress, anxiety and fear, giving a psychotherapeutic relief but did not completely remove the persistent fatigue experienced by the breast cancer patients. Thus, further investigation with long-term follow-up is recommended.

Plasma Cell Dyscrasia: A Case Series of a Masquerader.

Plasma cell dyscrasia is a result of an abnormal clonal proliferation of plasma cells. These cells arise from B cells in the bone marrow and produce immunoglobulins. Multiple myeloma is a type of plasma cell dyscrasia that commonly presents with symptoms secondary to hypercalcemia, hyperviscosity, renal failure, and bone pain. Here, we report three patients with unusual presentations of plasma cell dyscrasias.

Multicorrection Goldenhar syndrome (facio-auriculo-vertebral dysplasia): a rare follow-up case of 12-year-old female.

The MSX homeobox genes cause Goldenhar syndrome (GHS) or facio-auriculo-vertebral dysplasia, a rare developmental defect. Its exact etiology is still unknown. Its incidence lies between 1: 3500 and 1: 5600. In 85% of the cases, the unilateral face is affected. Typical clinical findings in a classic GHS include eye disorders, ear irregularities (with or without hearing loss), facial impairments, dental and oral ailments, cardiac syndromes, central nervous system (CNS) involvement, trachea and lung malformations, kidney and gastrointestinal defects, and skeletal alterations. This case report presents a follow-up case of Goldenhar Syndrome in a 12-year-old female, with no relevant family history, diagnosed with anotia on the left side, cyanosis, and facial asymmetry at birth. She presented with moderate growth failure, bilateral sclerosing mastoiditis and kyphoscoliosis. She underwent posterior scoliosis correction posterior instrumented fusion from D1 to D11.

Discovery of Halogenated Benzothiadiazine Derivatives with Anticancer Activity*.

Mitochondrial respiratory complex II (CII), also known as succinate dehydrogenase, plays a critical role in mitochondrial metabolism. Known but low potency CII inhibitors are selectively cytotoxic to cancer cells including the benzothiadiazine-based anti-hypoglycemic diazoxide. Herein, we study the structure-activity relationship of benzothiadiazine derivatives for CII inhibition and their effect on cancer cells for the first time. A 15-fold increase in CII inhibition was achieved over diazoxide, albeit with micromolar IC50 values. Cytotoxicity evaluation of the novel derivatives resulted in the identification of compounds with much greater antineoplastic effect than diazoxide, the most potent of which possesses an IC50 of 2.93±0.07 µM in a cellular model of triple-negative breast cancer, with high selectivity over nonmalignant cells and more than double the potency of the clinical agent 5-fluorouracil. No correlation between cytotoxicity and CII inhibition was found, thus indicating an as-yet-undefined mechanism of action of this scaffold. The derivatives described herein represent valuable hit compounds for therapeutic discovery in triple-negative breast cancer.

Discovery of a Potent and Selective PI3Kδ Inhibitor (S)-2,4-Diamino-6-((1-(7-fluoro-1-(4-fluorophenyl)-4-oxo-3-phenyl-4H-quinolizin-2-yl)ethyl)amino)pyrimidine-5-carbonitrile with Improved Pharmacokinetic Profile and Superior Efficacy in Hematological Cancer Models.

PI3Kδ inhibitors have been approved for B-cell malignancies like CLL, small lymphocytic lymphoma, and so forth. However, currently available PI3Kδ inhibitors are nonoptimal, showing weakness against at least one of the several important properties: potency, isoform selectivity, and/or pharmacokinetic profile. To come up with a PI3Kδ inhibitor that overcomes all these deficiencies, a pharmacophoric expansion strategy was employed. Herein, we describe a systematic transformation of a "three-blade propeller" shaped lead, 2,3-disubstituted quinolizinone 11, through a 1,2-disubstituted quinolizinone 20 to a novel "four-blade propeller" shaped 1,2,3-trisubstituted quinolizinone 34. Compound 34 has excellent potency, isoform selectivity, metabolic stability across species, and exhibited a favorable pharmacokinetic profile. Compound 34 also demonstrated a differentiated efficacy profile in human germinal center B and activated B cell-DLBCL cell lines and xenograft models. Compound 34 qualifies for further evaluation as a candidate for monotherapy or in combination with other targeted agents in DLBCLs and other forms of iNHL.

Probing structural requirements for human topoisomerase I inhibition by a novel N1-Biphenyl fluoroquinolone.

Fluoroquinolones substituted with N-1 biphenyl and napthyl groups were discovered to act as catalytically inhibitors of human topoisomerases I and II, and to possess anti-proliferative activity in vivo. Structural requirements for these novel quinolones to inhibit catalytic activity of human topoisomerase I have not been explored. In this work novel derivatives of the N-1 biphenyl fluoroquinolone were designed, synthesized and evaluated to understand structural requirements of the C-3 carboxylic acid, C-6 fluorine, C-7 aminomethylpyrrolidine, C-8 methoxy, and the N-1 biphenyl functional groups for hTopoI inhibition. Characterization of each analog for inhibition of hTopoI catalytic inhibition reveals critical insight into structural requirements of these novel quinolones for activity. Additionally, results of DNA binding and modeling studies suggest that N-1 biphenyl fluoroquinolones intercalate between the DNA base pairs with the N-1 biphenyl functional group, rather than the quinolone core, and that this mode of DNA intercalation contributes to inhibition of hTopoI by these novel structures. The results presented here support further development and evaluation of N-1 biphenyl fluoroquinolone analogs as a novel class of anti-cancer agents that act through catalytic inhibition of hTopoI.

Novel N-1 substituted fluoroquinolones inhibit human topoisomerase I activity and exhibit anti-proliferative activity.

Fluoroquinolone-class agents selectively target the bacterial type IIA topoisomerases DNA gyrase and topoisomerase IV, with a few exceptions that target eukaryotic type IIA topoisomerases. Fluoroquinolones bind and stabilize type IIA topoisomerase-DNA covalent complexes that contain a double-strand break. This unique mode of action is referred to as 'topoisomerase poisoning'. We discovered that two novel fluoroquinolones having aryl functionality at the N-1 position, UITT-3-217 (217) and UITT-3-227 (227), could inhibit the catalytic activity of human topoisomerase II without stabilizing topoisomerase-DNA complexes, i.e., without poisoning it. Surprisingly, these compounds are more effective in inhibiting the catalytic activities of human and bacterial topoisomerase I. The National Cancer Institute's 60 human tumor cell lines screen revealed significant anti-proliferative activities with 217 and 227 against the majority of 60 cancer cell lines. A proof of concept in vivo efficacy study using an HT-29 xenograft model of human colorectal cancer showed that 217 could inhibit the proliferation of human colorectal cancer cells to a degree comparable to fluorouracil in mice. Although 227 also exhibited anti-proliferative activity, it was not as effective as 217 in this xenograft model. These novel fluoroquinolones may serve as promising lead compounds for the development of new anticancer drugs.

Imitating Pathologist Based Assessment With Interpretable and Context Based Neural Network Modeling of Histology Images.

Convolutional neural networks (CNNs) have gained steady popularity as a tool to perform automatic classification of whole slide histology images. While CNNs have proven to be powerful classifiers in this context, they fail to explain this classification, as the network engineered features used for modeling and classification are ONLY interpretable by the CNNs themselves. This work aims at enhancing a traditional neural network model to perform histology image modeling, patient classification, and interpretation of the distinctive features identified by the network within the histology whole slide images (WSIs). We synthesize a workflow which (a) intelligently samples the training data by automatically selecting only image areas that display visible disease-relevant tissue state and (b) isolates regions most pertinent to the trained CNN prediction and translates them to observable and qualitative features such as color, intensity, cell and tissue morphology and texture. We use the Cancer Genome Atlas's Breast Invasive Carcinoma (TCGA-BRCA) histology dataset to build a model predicting patient attributes (disease stage and node status) and the tumor proliferation challenge (TUPAC 2016) breast cancer histology image repository to help identify disease-relevant tissue state (mitotic activity). We find that our enhanced CNN based workflow both increased patient attribute predictive accuracy (~2% increase for disease stage and ~10% increase for node status) and experimentally proved that a data-driven CNN histology model predicting breast invasive carcinoma stages is highly sensitive to features such as color, cell size, and shape, granularity, and uniformity. This work summarizes the need for understanding the widely trusted models built using deep learning and adds a layer of biological context to a technique that functioned as a classification only approach till now.

Building trans-omics evidence: using imaging and 'omics' to characterize cancer profiles.

Utilization of single modality data to build predictive models in cancer results in a rather narrow view of most patient profiles. Some clinical facet s relate strongly to histology image features, e.g. tumor stages, whereas others are associated with genomic and proteomic variations (e.g. cancer subtypes and disease aggression biomarkers). We hypothesize that there are coherent "trans-omics" features that characterize varied clinical cohorts across multiple sources of data leading to more descriptive and robust disease characterization. In this work, for l 05 breast cancer patients from the TCGA (The Cancer Genome Atlas), we consider four clinical attributes (AJCC Stage, Tumor Stage, ER-Status and PAM50 mRNA Subtypes), and build predictive models using three different modalities of data (histopathological images, transcriptomics and proteomics). Following which, we identify critical multi-level features that drive successful classification of patients for the various different cohorts. To build predictors for each data type, we employ widely used "best practice" techniques including CNN-based (convolutional neural network) classifiers for histopathological images and regression models for proteogenomic data. While, as expected, histology images outperformed molecular features while predicting cancer stages, and transcriptomics held superior discriminatory power for ER-Status and PAM50 subtypes, there exist a few cases where all data modalities exhibited comparable performance. Further, we also identified sets of key genes and proteins whose expression and abundance correlate across each clinical cohort including (i) tumor severity and progression (incl. GABARAP), (ii) ER-status (incl.ESRl) and (iii) disease subtypes (incl. FOXCl). Thus, we quantitatively assess the efficacy of different data types to predict critical breast cancer patient attributes and improve disease characterization.

Localized renal cystic disease.

Localized renal cystic disease (LRCD) is a rare benign non-hereditary, non-progressive condition which must be differentiated from other renal cystic diseases. Familiarity with this condition and its characteristic imaging features avoids unnecessary surgical intervention. We report a case of LRCD in a 40-year-old male who presented with left loin pain. Computed tomography demonstrated a cluster of simple cysts in the lower pole of the left kidney with normal right kidney and other organs. Diagnosis of LRCD was made on typical imaging characteristics and absence of family history of cystic renal disease.

Fetal MRI in the pre-operative diagnosis and assessment of secondary abdominal pregnancy: a rare sequela of a previous caesarean section.

Secondary abdominal pregnancy is a rare type of ectopic pregnancy. Following fertilization, the blastocyst escapes from the uterine cavity and implants in the peritoneal cavity. The early antenatal diagnosis and identification of the site and extent of placental implantation in an abdominal pregnancy are important to prepare for the eventual surgery. We present the case of a 24-year-old patient presenting with loss of fetal movement at 26 weeks of gestation for whom an abdominal pregnancy was suspected on ultrasonography and later confirmed on magnetic resonance imaging (MRI). She had one caesarean section in the past. The MRI findings suggested a scar dehiscence. She was eventually managed surgically, and the unviable fetus was removed. Abdominal pregnancies must be treated as emergencies. They usually present with complications such as fetal death and intra-abdominal hemorrhaging and can be easily missed on routine antenatal ultrasonography. The exact anatomical relationships of the fetus, the placenta, and vital maternal intra-abdominal structures can be accurately delineated with MRI, which greatly aids the management of patients with abdominal pregnancy. A proposed imaging protocol and technical suggestions for improving the diagnostic capability of ultrasonography and MRI in abdominal pregnancies have been provided to aid in the appropriate evaluation of suspect cases.

Insulin secretagogue, alpha-glucosidase and antioxidant activity of some selected spices in streptozotocin-induced diabetic rats.

Spices are extensively used to enhance the taste and flavor of foods and are known to possess several medicinal properties. Myristica fragrans, Parmelia perlata, Illicium verum, Trachyspermum copticum and Myristica malabarica, the commonly used spices in India were assessed for antidiabetic activity in streptozotocin induced diabetic rats. In the in vitro insulin secretion studies on isolated islets of Langerhans, M. fragrans, T. copticum and M. malabarica showed dose dependent insulin secretion. At 1 mg/ml, P. perlata showed significant in vitro alpha-glucosidase inhibitory activity with IC(50) value of 0.14 mg/ml followed by M. malabarica (0.64 mg/ml), I. verum (0.67 mg/ml), M. fragrans (0.85 mg/ml) and T. copticum (0.92 mg/ml). The DPPH free radical scavenging activity of the extracts at a concentration of 1 mg/ml was as M. malabarica (90.45%), M. fragrans (89.89%), I. verum (87.22%), P. perlata (76.70%) and T. copticum (38.14%). P. perlata showed the highest phenolic content (i.e., 118.5 mg gallic acid equivalents/g) followed by M. malabarica (84.13 mg gallic acid equivalents/g). M. malabarica showed the highest flavonoid content (i.e., 38.35 mg quercetin equivalents/g). Regular use of these spices may prevent postprandial rise in glucose levels through inhibition of intestinal alpha-glucosidase and may maintain blood glucose level through insulin secretagogue action.