Transformer-based decoder of melanoma classification using hand-crafted texture feature fusion and Gray Wolf Optimization algorithm.

Melanoma is a type of skin cancer that poses significant health risks and requires early detection for effective treatment. This study proposing a novel approach that integrates a transformer-based model with hand-crafted texture features and Gray Wolf Optimization, aiming to enhance efficiency of melanoma classification. Preprocessing involves standardizing image dimensions and enhancing image quality through median filtering techniques. Texture features, including GLCM and LBP, are extracted to capture spatial patterns indicative of melanoma. The GWO algorithm is applied to select the most discriminative features. A transformer-based decoder is then employed for classification, leveraging attention mechanisms to capture contextual dependencies. The experimental validation on the HAM10000 dataset and ISIC2019 dataset showcases the effectiveness of the proposed methodology. The transformer-based model, integrated with hand-crafted texture features and guided by Gray Wolf Optimization, achieves outstanding results. The results showed that the proposed method performed well in melanoma detection tasks, achieving an accuracy and F1-score of 99.54% and 99.11% on the HAM10000 dataset, and an accuracy of 99.47%, and F1-score of 99.25% on the ISIC2019 dataset. • We use the concepts of LBP and GLCM to extract features from the skin lesion images. • The Gray Wolf Optimization (GWO) algorithm is employed for feature selection. • A decoder based on Transformers is utilized for melanoma classification.

Role of End Plate Changes and Paraspinal Muscle Pathology in Lower Back Pain: A Narrative Review.

Degenerative changes of the lumbar intervertebral disc are the most significant causes of enduring lower back pain. The possibility of the diagnosis is limited in people with this low back pain. Therefore, it is essential to identify the relevant back pain subgroups. The paraspinal muscles, that is, the muscles that attach to the spine, are necessary for the proper functioning of the spine and the body; insufficiency can result in back pain. Lower back pain disorders are strongly associated with altered function or structure of these paraspinal muscles, especially fibrosis and fatty infiltration. Modic changes are the bone marrow changes of the end plate in the vertebral body seen on MRI. These are strongly related to degeneration of the disc and are common in individuals with back pain symptoms. Articles were selected from Google Scholar using the terms 'Modic changes,' 'end plate changes,' 'paraspinal muscles,' and 'lower back pain. ' This article compiled different studies aiming to enhance the comprehension of biochemical processes resulting in the development of lumbar pain. Search using the keywords 'Modic changes,'' end plate changes lower back pain,' 'paraspinal muscles lower back pain,' and 'Modic changes lower back pain' on Google Scholar yielded 33000, 41000, 49400, and 17,800 results, and 958, 118, 890 and 560 results on Pubmed respectively.

Research on image recognition of tomato leaf diseases based on improved AlexNet model.

Aiming at the problems that the traditional image recognition technology is challenging to extract useful features and the recognition time is extended; the AlexNet model is improved to improve the effect of image classification and recognition. This study focuses on 8 types of tomato leaf diseases and healthy leaves. By using HOG and LBP weighted fusion to extract image features, a tomato leaf disease recognition model based on the AlexNet model is proposed, and transfer learning is used to train the AlexNet model. Transfer the knowledge learned by the AlexNet model on the PlantVillage image dataset to this model while reducing the number of fully connected layers. Keras deep learning framework and programming language Python were used. The model was implemented, and the classification and identification of tomato leaf diseases were carried out. The recognition rate of feature-weighted fusion classification is higher than that of serial and parallel methods, and the recognition time is the shortest. When the weight coefficient ratio of HOG and LBP is 3:7, the image recognition rate is the highest, and its value is 97.2 %. From the model performance curve See, when the number of iterations is more than 150 times, the training set and test accuracy rate both exceed 97 %, the loss rate shows a gradient decline, and the change is relatively stable; compared with the traditional AlexNet model, HOG + LBP + SVM model, and VGG model, improved AlexNet model has the highest recognition rate, and it has high recall value, accuracy, and F1 value; Compared with the latest convolutional neural network disease recognition models, improved AlexNet model recognition accuracy was 98.83 %, and the F1 value was 0.994. It shows that the model has good convergence performance, fast prediction speed, and low loss rate and can effectively identify 8 types of tomato leaf images, which provides a reference for the research on crop disease identification.

Effects of Multimodal Physical Therapy on Pain, Disability, H-reflex, and Diffusion Tensor Imaging Parameters in Patients With Lumbosacral Radiculopathy Due to Lumbar Disc Herniation: A Preliminary Trial.

Background Lumbosacral radiculopathy (LSR) due to lumbar disc herniation (LDH) is a condition caused by mechanical compression of nerve roots. Various physical therapy interventions have been proposed for the conservative management of LSR due to LDH. However, the study of physical therapy interventions in a multimodal form is lacking. Additionally, the effect of physical therapy on diffusion tensor imaging (DTI) parameters of the compressed nerve root has not been studied. This study aimed to investigate the effects of multimodal physical therapy (MPT) on pain, disability, soleus H-reflex, and DTI parameters of the compressed nerve root in patients with chronic unilateral LSR due to LDH. Methods A prospective preliminary pre-post clinical trial with a convenience sample was conducted. A total of 14 patients with chronic unilateral LSR due to paracentral L4-L5 or L5-S1 LDH were recruited for the study. Participants received a total of 18 sessions of a six-week MPT program that consisted of electrophysical agents, manual therapy interventions, and core stability exercises. Electrophysical agents involved interferential current and hot pack. Manual therapy interventions included myofascial release, side posture positional distraction, passive spinal rotation mobilization, and high-velocity low-amplitude manipulation. Visual analog scale (VAS), Roland-Morris Disability Questionnaire (RMDQ), soleus H-reflex amplitude, side-to-side amplitude (H/H) ratio, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) of the compressed nerve root were measured at baseline and post-intervention. Results There were significant improvements in VAS, RMDQ, H/H ratio, FA, and ADC of the compressed nerve root. Furthermore, significant improvement was found in the affected side compared with the contralateral side in H-reflex amplitude. Conclusions The observations of this preliminary trial suggest that MPT is a successful intervention in patients with chronic unilateral LSR due to LDH. Regarding DTI parameters of the compressed nerve root, FA increased and ADC decreased. Future studies with a control group, large sample sizes, and longer follow-up periods are needed.

Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.

Citrus fruits are extensively cultivated fruits with high nutritional value. The identification of distinct ripeness stages in citrus fruits plays a crucial role in guiding the planning of harvesting paths for citrus-picking robots and facilitating yield estimations in orchards. However, challenges arise in the identification of citrus fruit ripeness due to the similarity in color between green unripe citrus fruits and tree leaves, leading to an omission in identification. Additionally, the resemblance between partially ripe, orange-green interspersed fruits and fully ripe fruits poses a risk of misidentification, further complicating the identification of citrus fruit ripeness. This study proposed the YOLO-CIT (You Only Look Once-Citrus) model and integrated an innovative R-LBP (Roughness-Local Binary Pattern) method to accurately identify citrus fruits at distinct ripeness stages. The R-LBP algorithm, an extension of the LBP algorithm, enhances the texture features of citrus fruits at distinct ripeness stages by calculating the coefficient of variation in grayscale values of pixels within a certain range in different directions around the target pixel. The C3 model embedded by the CBAM (Convolutional Block Attention Module) replaced the original backbone network of the YOLOv5s model to form the backbone of the YOLO-CIT model. Instead of traditional convolution, Ghostconv is utilized by the neck network of the YOLO-CIT model. The fruit segment of citrus in the original citrus images processed by the R-LBP algorithm is combined with the background segment of the citrus images after grayscale processing to construct synthetic images, which are subsequently added to the training dataset. The experiment showed that the R-LBP algorithm is capable of amplifying the texture features among citrus fruits at distinct ripeness stages. The YOLO-CIT model combined with the R-LBP algorithm has a Precision of 88.13%, a Recall of 93.16%, an F1 score of 90.89, a mAP@0.5 of 85.88%, and 6.1ms of average detection speed for citrus fruit ripeness identification in complex environments. The model demonstrates the capability to accurately and swiftly identify citrus fruits at distinct ripeness stages in real-world environments, effectively guiding the determination of picking targets and path planning for harvesting robots.

Effect of Quadratus Lumborum Block in Patients With Acute-Subacute Unilateral Lumbar Strain.

INTRODUCTION: Lumbar strain originating from the quadratus lumborum (QL) is an important cause of low back pain; however, its diagnosis is often missed, and treatment is often inadequate. This leads to unnecessary diagnostic investigations and chronicization of pain. Therefore, it is important to treat it effectively and safely. In this study, we aimed to find out the effect of ultrasound (US)-guided QL block in acute-subacute low back pain caused by a strain of QL. MATERIALS AND METHODS: Our study was retrospective, and the changes in the visual analog scale (VAS) and Oswestry Disability Index (ODI) scores within one week in 50 patients with acute-subacute localized low back pain, unilateral lumbar strain, palpation tenderness, paravertebral spasm, and decreased lumbar range of motion in the QL muscle, in whom we applied US-guided block to the QL muscle, were analyzed. RESULTS: There was a significant decrease in the mean VAS and ODI scores of the patients after the procedure. There was a negative correlation between improvement rates in VAS and ODI scores and age and body mass index (BMI). Recovery rates were higher in female patients than in male patients. CONCLUSION: It can be said that US-guided QL block is an effective treatment method for QL-induced lumbar strains, and younger age, female gender, and lower BMI are associated with better responses after injection.

Evaluation of the Relationship Between Smartphone Addiction and Lower Back Pain and Neck Pain Among Medical Students at Al-Baha University.

Introduction In recent years, the increased use of smartphones has adversely affected students, leading to issues like musculoskeletal pain. Therefore, our objective was to assess the correlation between smartphone addiction and neck and lower back pain. Methodology An observational cross-sectional study was conducted at Al-Baha University, Al-Baha, Saudi Arabia. The Smartphone Addiction Scale Short Version (SAS-SV) was used to measure the level of smartphone addiction while the Nordic Musculoskeletal Questionnaire (NMQ) was utilized to evaluate musculoskeletal pain. Results Smartphone addiction was prevalent in 72% of the participants (n = 293). Significantly, lower back pain was associated with smartphone addiction (p-value = 0.004). However, none of the demographic characteristics were associated with neck or lower back pain (p-value > 0.05). Students in clinical years had a higher risk of neck pain than those in an internship (p-value = 0.048). Conclusion Almost two-thirds of the students were addicted to smartphones, with a significant association with lower back pain. Students addicted to their smartphones had a higher risk of developing lower back pain, while clinical-year students had a higher risk of developing neck pain. It's important to raise awareness about the health and safety dangers linked to smartphones and other devices.

The Association of Intestinal Leak with Sarcopenia and Physical Disability in Patients with Various Stages of Chronic Kidney Disease.

Sarcopenia is related to disease severity in chronic kidney disease (CKD) patients; however, its pathophysiology remains poorly known. We investigated the associations of biomarkers of intestinal leak with sarcopenia in various stages of CKD. We recruited 61-76-year-old male controls and patients with various stages of CKD (n = 36-57/group) for measuring plasma lipopolysaccharide-binding protein (LBP) and zonulin (markers of intestinal leak), handgrip strength (HGS), skeletal mass index (SMI), and gait speed (markers of sarcopenia), and short physical performance battery (SPPB; marker of physical capacity). CKD stages 4 and 5 were associated with lower HGS, SMI, gait speed, and cumulative SPPB scores and a higher sarcopenia prevalence than controls and patients with CKD stages 1 and 2 (all p < 0.05). CKD patients (stages 1 and 2) had elevated plasma zonulin and LBP when compared with CKD stages 4 and 5. Plasma zonulin and LBP exhibited significant correlations with renal function, HGS, gait speed, SPPB scores, and oxidative stress markers in CKD stages 4 and 5 (all p < 0.05). However, similar relations were not found in early CKD. Collectively, intestinal leak may be contributing to sarcopenia and physical disability in the advanced stages of CKD.

The high-throughput solid-phase extraction of cis-cyclo(L-Leu-L-Pro) and cis-cyclo(L-Phe-L-Pro) from Lactobacillus plantarum demonstrates efficacy against multidrug-resistant bacteria and influenza A (H3N2) virus.

Introduction: 2,5-diketopiperazines are the simplest forms of cyclic dipeptides (CDPs) and have diverse frameworks with chiral side chains that are useful for drug development. Previous research has investigated the antimicrobial properties of proline-linked CDPs and their combinations in the culture filtrate (CF) of Lactobacillus plantarum LBP-K10 using anion exchange chromatography (AEC). However, the quantity of CDPs showcasing notable anti-influenza virus activity derived from AECs was generally lower than those originating from Lactobacillus CF. Methods: To address this issue, the study aims to propose a more efficient method for isolating CDPs and to introduce the antiviral combinations of CDPs obtained using a new method. The study employed a novel technique entailing high-throughput C18-based solid-phase extraction with a methanol gradient (MeSPE). The MeSPE method involved increasing the methanol concentration from 5% to 50% in 5% increments. Results: The methanol SPE fractions (MeSPEfs) eluted with methanol concentrations between 35% and 45% evinced substantial efficacy in inhibiting the influenza A/H3N2 virus via plaque-forming assay. MeSPEf-45, the 45% MeSPEf, exhibited exceptional efficacy in preventing viral infections in Madin-Darby kidney cells, surpassing both individual CDPs and the entire set of MeSPEfs. To identify the specific antiviral components of MeSPEf-45, all MeSPEfs were further fractionated through preparative high-performance liquid chromatography (prep-HPLC). MeSPEf-45 fractions S8 and S11 presented the highest activity against multidrug-resistant bacteria and influenza A/H3N2 virus among all MeSPEfs, with 11 common fractions. Antiviral fractions S8 and S11 were identified as proline-based CDPs, specifically cis-cyclo(L-Leu-L-Pro) and cis-cyclo(L-Phe-L-Pro), using gas chromatography-mass spectrometry. The combination of MeSPEf-45 fractions S8 and S11 displayed superior antibacterial and anti-influenza virus effects compared to the individual fractions S8 and S11. Discussion: High-throughput MeSPE-derived MeSPEfs and subsequent HPLC-fractionated fractions presents an innovative approach to selectively purify large amounts of potent antimicrobial CDPs from bacterial CF. The findings also show the effectiveness of physiologically bioactive combinations that utilize fractions not containing CDP. This study provides the initial evidence demonstrating the antimicrobial properties of CDPs acquired through high-throughput SPE techniques.

Past, present, and future of microbiome-based therapies.

Technological advances in studying the human microbiome in depth have enabled the identification of microbial signatures associated with health and disease. This confirms the crucial role of microbiota in maintaining homeostasis and the host health status. Nowadays, there are several ways to modulate the microbiota composition to effectively improve host health; therefore, the development of therapeutic treatments based on the gut microbiota is experiencing rapid growth. In this review, we summarize the influence of the gut microbiota on the development of infectious disease and cancer, which are two of the main targets of microbiome-based therapies currently being developed. We analyze the two-way interaction between the gut microbiota and traditional drugs in order to emphasize the influence of gut microbial composition on drug effectivity and treatment response. We explore the different strategies currently available for modulating this ecosystem to our benefit, ranging from 1st generation intervention strategies to more complex 2nd generation microbiome-based therapies and their regulatory framework. Lastly, we finish with a quick overview of what we believe is the future of these strategies, that is 3rd generation microbiome-based therapies developed with the use of artificial intelligence (AI) algorithms.

Evolving Spinal Treatment Modalities: A Review of the Literature on Non-surgical Interferential Differential Dynamics (IDD) Therapy.

Low back pain is one of the most common ailments encountered by physicians and orthopedic surgeons. There are various modalities used to treat low back pain, including conservative management, and a few of them involve rest, medications, massage, bracing, acupuncture, and physical therapy. Though most of the patients improve with conservative management, the burden of this disease has been very high and caused a significant amount of economic loss. Therefore, in-depth knowledge of all conservative methods is essential for physicians managing low back pain. Furthermore, there can be many causes of low back pain. Some of the more common ones are mechanical back pain due to paraspinal muscles or facetal in origin, discogenic back pain, and sacroiliac joint dysfunction. Many patients, especially the older population, have the discogenic origin as the more common cause of back pain, and traction therapy has been used for its treatment for ages. In this review, we discuss non-surgical spinal decompression/traction therapy popularly known as interferential differential dynamics (IDD) therapy with its current standing and recent advancement.

Low back pain prevention behaviors and beliefs among the Polish population in a cross-sectional survey.

Background: Low back pain (LBP) is one of the most common problems of public health and creates a burden globally. The aim was to assess the Polish population's back pain prevention behaviors and beliefs and to examine how these health behaviors and beliefs vary across sociodemographic factors and physical activity. Methods: A cross-sectional survey was carried out among 208 randomly selected patients of the public general practitioner clinic. The differences in LBP-related beliefs and attitudes were determined due to participants' status of requiring or non-requiring LBP treatment. Results: More than half of the respondents did not engage in behaviors that protect against back pain. Individuals with higher education levels and those who exercised at least once a week were significantly more likely to adopt behaviors to protect their backs. Less than half of the participants reported having a workplace that was adequately prepared to protect against back pain, and only 35.1% of the participants reported receiving instruction while taking up work on how to avoid back pain while working. According to respondents' opinions, preventive actions are necessary to protect against back pain. Inappropriate exercises and stress can be contributors to back pain, with these opinions reported more often by women and participants with higher education levels. Participants who received treatment for LBP showed a significantly higher expression of behaviors to protect against back pain compared to participants who did not require treatment. However, there were no significant differences in participants' beliefs about back pain prevention between the group requiring LBP treatment and the group not requiring LBP treatment. Conclusion: The study provides valuable insights into the association between LBP treatment, back pain prevention behaviors, and beliefs, suggesting potential avenues for future research and intervention development. By addressing workplace ergonomics and promoting a culture of back health, it may be possible to reduce the burden of LBP in Poland.

Effect of Lycium barbarum polysaccharide on osteoblast proliferation and differentiation in postmenopausal osteoporosis.

OBJECTIVE: We aimed to investigate the effect of Lycium barbarum polysaccharide (LBP) on the proliferation and differentiation of osteoblasts in postmenopausal individuals with osteoporosis using in vitro cell experiments. METHODS: We assessed the effect of long-term LBP consumption on the intestinal metabolites of individuals using a simulation of the human intestinal microbiota ecosystem. We also tested the capacity of LBP in proliferating MC3T3-E1 cells using the cell counting kit-8 (CCK-8) method and analyzed the effect of intestinal metabolites on the osteogenic differentiation of MC3T3-E1 cells by testing bone metabolism viability with relevant indicators. RESULTS: The level of short-chain fatty acids (SCFAs) significantly increased (p < 0.05), and the concentrations of acetic acid, propionic acid, and butyric acid all showed an upward trend after the treatment using LBP. At appropriate concentrations, the fermentation supernatant can enhance osteoblast proliferation by significantly increasing the active expression of bone-alkaline phosphatase (B-ALP) and osteocalcin (OCN) in osteoblasts (p < 0.05). CONCLUSION: By modulating the metabolites of intestinal microbiota, production of SCFAs, the prebiotic properties of LBP can enhance osteoblast differentiation through in vitro simulation experiment and cell-based assay.

HO-SsNF: heap optimizer-based self-systematized neural fuzzy approach for cervical cancer classification using pap smear images.

Cervical cancer is a significant concern for women, necessitating early detection and precise treatment. Conventional cytological methods often fall short in early diagnosis. The proposed innovative Heap Optimizer-based Self-Systematized Neural Fuzzy (HO-SsNF) method offers a viable solution. It utilizes HO-based segmentation, extracting features via Gray-Level Co-Occurrence Matrix (GLCM) and Local Binary Pattern (LBP). The proposed SsNF-based classifier achieves an impressive 99.6% accuracy in classifying cervical cancer cells, using the Herlev Pap Smear database. Comparative analyses underscore its superiority, establishing it as a valuable tool for precise cervical cancer detection. This algorithm has been seamlessly integrated into cervical cancer diagnosis centers, accessible through smartphone applications, with minimal resource demands. The resulting insights provide a foundation for advancing cancer prevention methods.

Biochemical, Hematological, Inflammatory, and Gut Permeability Biomarkers in Patients with Alcohol Withdrawal Syndrome with and without Delirium Tremens.

Background: Delirium Tremens (DT) is known to be a serious complication of alcohol withdrawal syndrome (AWS). Neurotransmitter abnormalities, inflammation, and increased permeability are associated with the pathogenesis of AWS and DT. However, the biomarkers of these conditions are still poorly understood. Methods: In this work, biochemical, hematologic, inflammatory, and gut permeability biomarkers were investigated in the following three groups: healthy controls (n = 75), severe AWS patients with DT (n = 28), and mild/moderate AWS without DT (n = 97). Blood sampling was performed after resolution of the acute condition (on 5 ± 1 day after admission) to collect clinical information from patients and to investigate associations with clinical scales. Biomarker analysis was performed using automated analyzers and ELISA. Inflammatory biomarkers included the erythrocyte sedimentation rate (ESR), high-sensitivity C-reactive protein (hsCRP), and platelet-to-lymphocyte ratio (PLR). Results: Among the biochemical biomarkers, only glucose, total cholesterol, and alanine aminotransferase (ALT) changed significantly in the analyzed groups. A multiple regression analysis showed that age and ALT were independent predictors of the CIWA-Ar score. Hematologic biomarker analysis showed an increased white blood cell count, and the elevated size and greater size variability of red blood cells and platelets (MCV, RDWc, and PDWc) in two groups of patients. Gut permeability biomarkers (FABP2, LBP, and zonulin) did not change, but were associated with comorbid pathologies (alcohol liver disease and pancreatitis). The increase in inflammatory biomarkers (ESR and PLR) was more evident in AWS patients with DT. Cluster analysis confirmed the existence of a subgroup of patients with evidence of high inflammation, and such a subgroup was more frequent in DT patients. Conclusions: These findings contribute to the understanding of biomarker variability in AWS patients with and without DT and support the heterogeneity of patients by the level of inflammation.

Human and Porcine Lumbar Endplate Injury Risk in Repeated Flexion-Compression.

Low back pain (LBP) affects 50-80% of adults at some point in their lifetime, yet the etiology of injury is not well understood. Those exposed to repeated flexion-compression are at a higher risk for LBP, such as helicopter pilots and motor vehicle operators. Animal injury models offer insight into in vivo injury mechanisms, but interspecies scaling is needed to relate animal results to human. Human (n = 16) and porcine (n = 20) lumbar functional spinal units (FSUs) were loaded in repeated flexion-compression (1 Hz) to determine endplate fracture risk over long loading exposures. Flexion oscillated from 0 to 6° and peak applied compressive stress ranged from 0.65 to 2.38 MPa for human and 0.64 to 4.68 MPa for porcine specimens. Five human and twelve porcine injuries were observed. The confidence intervals for human and porcine 50% injury risk curves in terms of stress and cycles overlapped, indicating similar failure behavior for this loading configuration. However, porcine specimens were more tolerant to the applied loading compared to human, demonstrated by a longer time-to-failure for the same applied stress. Optimization revealed that time-to-failure in human specimens was approximately 25% that of porcine specimens at a given applied stress within 0.65-2.38 MPa. This study determined human and porcine lumbar endplate fracture risks in long-duration repeated flexion-compression that can be directly used for future equipment and vehicle design, injury prediction models, and safety standards. The interspecies scale factor produced in this study can be used for previous and future porcine lumbar injury studies to scale results to relevant human injury.

Effective prediction of human skin cancer using stacking based ensemble deep learning algorithm.

Automated diagnosis of cancer from skin lesion data has been the focus of numerous research. Despite that it can be challenging to interpret these images because of features like colour illumination changes, variation in the sizes and forms of the lesions. To tackle these problems, the proposed model develops an ensemble of deep learning techniques for skin cancer diagnosis. Initially, skin imaging data are collected and preprocessed using resizing and anisotropic diffusion to enhance the quality of the image. Preprocessed images are fed into the Fuzzy-C-Means clustering technique to segment the region of diseases. Stacking-based ensemble deep learning approach is used for classification and the LSTM acts as a meta-classifier. Deep Neural Network (DNN) and Convolutional Neural Network (CNN) are used as input for LSTM. This segmented images are utilized to be input into the CNN, and the local binary pattern (LBP) technique is employed to extract DNN features from the segments of the image. The output from these two classifiers will be fed into the LSTM Meta classifier. This LSTM classifies the input data and predicts the skin cancer disease. The proposed approach had a greater accuracy of 97%. Hence, the developed model accurately predicts skin cancer disease.

Unveiling the Efficacy of Physiotherapy Strategies in Alleviating Low Back Pain: A Comprehensive Review of Interventions and Outcomes.

Low back pain (LBP) presents a significant burden globally, affecting individuals of all ages, but it is more common in adults aged 30-60 years old and demographics including race, ethnicity, and socioeconomic status. Physiotherapy interventions are commonly employed to manage LBP due to their non-invasive nature and potential for addressing underlying biomechanical dysfunctions. This comprehensive review aims to evaluate the efficacy of various physiotherapy strategies in alleviating LBP, considering a range of interventions and their associated outcomes. Through a thorough examination of existing literature from January 2017 to October 2023, this review synthesises evidence on the effectiveness of interventions such as manual therapy, exercise therapy, electrotherapy modalities, and education-based approaches. The review also scrutinizes the comparative effectiveness of different physiotherapy modalities and their suitability for specific patient populations, considering factors such as chronicity, severity, and underlying pathology. By critically evaluating the evidence base, this review aims to provide insights into the most effective physiotherapy strategies for alleviating LBP, chronic low back pain (CLBP) and chronic nonspecific low back pain (CNLBP) and guiding clinical practice toward evidence-based interventions. The Visual Analogue Scale and Numerical Pain Rating Scale for pain, Oswestry Disability Index and Roland-Morris Disability Questionnaire for disability, Modified-Modified Schober Test for measurement of lumbar flexion and extension and static and dynamic balance for assessing postural stability and balance were among the measures used to foresee enhancements in pain, disability, balance, and LBP symptoms. Twenty-one studies that fulfilled the criteria for inclusion (aged 20 to 50 years and of both genders) were added to the review. Exercises for core stability, strengthening, orthosis (a medical device designed to support, align, stabilise, or correct musculoskeletal structures and functions), transcutaneous electrical nerve stimulation, heat massage therapy, interferential current (a form of electrical stimulation used in physical therapy), Mulligan's mobilization (a manual therapy technique), low-level laser therapy, and McGill stabilization exercises (core exercises) were among the therapeutic strategies. The McKenzie method (back exercises), ultrasound, sensory-motor training, Swiss ball exercises, and other techniques reduced pain and enhanced strength, balance, and ease of daily activities. Every therapeutic approach has an impact on recovery rates ranging from minimal to maximal. Conventional physical therapy is less effective than most recent advanced techniques like mobilisation and exercises. In summary, the integration of manual techniques, orthoses and alternative intervention strategies with conservative therapeutic approaches can effectively alleviate pain, enhance function and yield better overall outcomes. To get more information about the optimal dosage, therapeutic modalities and long-term effects of these treatments, more admirable research is required. This paper aims to expand the scientific discourse by exploring non-traditional physiotherapy interventions and assessing their efficacy in light of the rigorous standards set forth by the latest WHO guidelines.

Mast Cells and Their Related Gene HK-1 are Closely Associated with Discogenic Low Back Pain: A Bioinformatics and Clinical Sample Study.

Background: Low back pain (LBP) is primarily caused by intervertebral disc degeneration (IVDD). Immune cells penetrating nucleus pulposus (NP) tissues may play an important role in generating IVDD and LBP. Methods: The clinical data from 100 cases of IVDD patients was initially analyzed retrospectively. Subsequently, peripheral blood and NP tissues from 41 IVDD patients were gathered for a validated investigation. Among them, ribosome-removed-RNA sequencing (RNA-seq) was performed on 10 cases of NP tissues of specific classifications (VAS 3 and Pfirrmann 3 were used as the controls, while patients with VAS 6 and Pfirrmann 5 were used as the experimental group). Differentially expressed genes (DEGs) were identified for the subsequent bioinformatics analysis. Further methods to confirm the underlying cause of discogenic LBP included mast cell immunohistochemistry (IHC), 12 cytokine detection, Western blot (WB), and real-time polymerase chain reaction (RT-PCR). Results: Discogenic LBP and IVDD severity are strongly associated, and immunological cell infiltration has been demonstrated to be a significant factor in LBP by bioanalytical research. Tryptase-positive mast cells were found to be significantly more abundant in the VAS 6 NP tissues of IVDD patients than in the VAS 3 NP tissues. It was initially demonstrated that IVDD and LBP were significantly impacted by hemokinin-1 (HK-1), the mast cell-related gene. Furthermore, blood levels of interleukin 12 p70 (IL-12P70) are noticeably elevated and strongly correlated with HK-1, indicating that HK-1 may be involved in the regulation of mast cell activity and IL-12P70 production. Conclusion: The severity of LBP was observed to be positively correlated with the IVDD Pfirrmann grading. Further research indicates that patients with IVDD may experience persistent low back pain due to HK-1 activation of mast cells and the release of the cytokine IL12P70. This work will offer new insights into the diagnosis and treatment of discogenic LBP.

Assessment of occupational musculoskeletal disorders (MSDs) among heavy vehicle drivers.

BACKGROUND: Professional driving requires long hours of work, uncomfortable seats, negotiating rough terrain and highways, and possibly minor repairs and other auxiliary transportation duties. Heavy vehicle drivers driving vehicles such as trucks, bulldozers, etc. due to such working structures are more prone to various musculoskeletal disorders (MSDs) and pain, which is of great concern. OBJECTIVES: In the present study, it is planned to investigate possible ergonomic risk factors such as age, weight, driving exposure, seat suspension systems, lifting heavy weights causing MSDs in drivers of various heavy vehicles. The results of the study are expected to help drivers reduce the risk of MSDs. METHODS: For the present study, the Nordic questionnaire on musculoskeletal disorders was modified and standardized and was administered to the 48 heavy vehicle drivers randomly selected to collect the data. RESULTS: The analysis divulged that over the past 12 months, lower back pain (LBP) emerged as the most dominant pain experienced by 56% of drivers, followed by knee pain (KP) (43%) and neck pain (NP) (39%) respectively. The prevalence of shoulder pain (SP) was observed to be much lower than in previous literature. The logistic regression model further revealed that increasing age, poor suspension system and poor body posture were significantly associated with lower back pain. Additionally, a poor suspension system and lifting heavy weights had significant effect on the drivers' knee pain. CONCLUSION: The results demonstrated the evident necessity for ergonomic consideration in vehicle designing and ergonomic training for heavy vehicle drivers.