Clinical and genetic investigation of 14 families with various forms of short stature syndromes.

Skeletal dysplasias are a heterogeneous group of disorders presenting mild to lethal defects. Several factors, such as genetic, prenatal, and postnatal environmental may contribute to reduced growth. Fourteen families of Pakistani origin, presenting the syndromic form of short stature either in the autosomal recessive or autosomal dominant manner were clinically and genetically investigated to uncover the underlying genetic etiology. Homozygosity mapping, whole exome sequencing, and Sanger sequencing were used to search for the disease-causing gene variants. In total, we have identified 13 sequence variants in 10 different genes. The variants in the HSPG2 and XRCC4 genes were not reported previously in the Pakistani population. This study will expand the mutation spectrum of the identified genes and will help in improved diagnosis of the syndromic form of short stature in the local population.

Design and synthesis of novel dihydropyridine- and benzylideneimine-based tyrosinase inhibitors.

Tyrosinase (TYR) inhibitors are very significant as they inhibit enzyme tyrosinase activity, and its inhibition is vital for skin care, anticancer medication, and antibrowning of fruits and vegetables. This work presents a novel and economical route for the preparation of new synthetic tyrosinase inhibitors using amlodipine (4). The novel conjugates 6 (a-o) were designed, synthesized, and characterized by spectroscopic analyses, including Fourier transform infrared and low- and high-resolution mass spectroscopy. The purified compound 4 was refluxed with various aldehydes and ketones 5 (a-o) for 5-8 h in methanol at 60°C-90°C. This research modified the drug in a step-by-step manner to develop therapeutic properties as a tyrosinase inhibitor. The structures of synthesized ligands 6 (a-o) were established based on spectral and analytical data. The synthesized compounds 6 (a-o) were screened against tyrosinase enzyme. Kojic acid was taken as standard. All the prepared compounds 6 (a-o) have good inhibition potential against the enzyme tyrosinase. Compounds 6o, 6b, 6f, and 6k depicted excellent antityrosinase activity. Compound 6k, with an IC50 value of 5.34 ± 0.58 µM, is as potent as the standard kojic acid (IC50 6.04 ± 0.11 µM), standing out among all synthesized compounds 6 (a-o). The in silico studies of the conjugates 6 (a-o) were evaluated via PatchDock. Compound 6k showed a binding affinity score of 8,999 and an atomic contact energy (ACE) value of -219.66 kcal/mol. The structure-activity relationship illustrated that the presence of dihydropyridine nuclei and some activating groups at the ortho and para positions of the benzylideneimine moiety is the main factor for good tyrosinase activity. The compound 6k could be used as a lead compound for drug modification as a tyrosinase inhibitor for skin care, anticancer medication, and antibrowning for fruits and vegetables.

Fractional analysis of non-linear fuzzy partial differential equations by using a direct procedure.

In this study, an accurate analytical solution is presented for fuzzy FPDEs. It is done by using a novel method called the Laplace-residual power series (LRPSM) to build a series solution to the given problems. The fundamental instruments of the employed method are the Laplace transform, fractional Laurent, and fractional power series. Using the idea of a limit at infinity, we provide a series solution to a fuzzy FPDE with quick convergence and simple coefficient finding. We analyze three cases to obtain approximate and exact solutions to show the effectiveness and reliability of the Laplace- residual power series approach. To demonstrate the accuracy of the suggested procedure, we compare the findings to the real data.

Exploring the Differential Effects of Transcranial Direct Current Stimulation: A Comparative Analysis of Motor Cortex and Cerebellar Stimulation.

Background: Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique. Constant electric current is passed through the patient's scalp with the aim of modulating cortical excitability. Stroke is a cerebrovascular disease characterized by hemorrhage or cerebral ischemia. This systematic review and meta-analysis are aimed at comparing the efficacy of motor cortex stimulation with that of cerebellar stimulation by using transcranial direct current stimulation. Method: Google Scholar, PubMed, EMBASE, Cochrane CENTRAL, and Physiotherapy Evidence Database (Pedro) databases were searched for studies. The extracted qualitative data was synthesized systematically. Cochrane RevMan software was used to conduct a meta-analysis of quantitative data. The fixed effects mean difference of the collected data was calculated at a 95% confidence interval (CI) for the changes in balance and side effects. Results: This research included 10 articles with seven studies assessing changes in balance (outcome measured in CoP and FMA scores) and side effects (tingling and itching were the most prevalent). There was no significant difference between the efficacy levels of m1-tDCS versus ctDCS (P = 0.18), m1-tDCS versus sham (P = 0.92), and ctDCS versus sham (P = 0.19). Itching and tingling sensation were the most common and were significantly prevalent in sham interventions (P < 0.00001). Conclusion: We found that motor cortex and cerebellar stimulations are both effective in improving motor function in stroke patients. There are no adverse effects to using the interventions besides mild itching and tingling experienced during the stimulation.

Application of coconut shell activated carbon filter in vertical subsurface flow constructed wetland for enhanced multi-metal bioremediation and antioxidant response of Salvinia cucullate.

Coconut shell activated carbon (CNSAC) was applied as a filter layer in hybrid vertical subsurface flow constructed wetland (H-VSSF-CW), in order to enhance the multi-metal removal efficiency of the constructed wetland (CW) and to reduce heavy metal accumulation on Salvinia cucullata. Treatment P + AC, (having CNSAC filter layer), showed 32, 21 and 34% more Cd, Cr, and Pb removal efficiency than treatment P (without CNSAC layer). CNSAC activated carbon adsorbed Cd and Pb and Cr by functional groups -NH, -NO2, -C-O, -OH and -CO, and significantly reduced Cd and Pb exposure to S. cucullate. Chromium adsorption by CNSAC filter layer was half (just 25% of total input) of the Cd and Pb. In treatment P, due to high Cd, Pb and Cr accumulation in S. cucullate, the antioxidant defense mechanism of the plant was collapsed and cell death was observed, which in turn has resulted reduced biomass gain (5% reduction). On the other hand, in treatment P + AC, an antioxidant defense mechanism was active in the form significantly (p ≤ 0.05) increased of SOD, CAT and proline content while reduced MDA, EL, %EB and soluble sugar. So, the application of CNSAC increased the heavy metal removal efficiency of H-VSSF-CW by adsorption of a considerable share of heavy metal and hence, reduced the heavy metal load/exposure to S. cucullate.

Gut microbiome as a treatment in colorectal cancer.

BACKGROUND: The gut microbiome plays a role in the development and progression of colorectal cancer (CRC). AIM AND OBJECTIVE: This review focuses on whether the gut microbiome is involved in the development and regulation of the host immune system. METHODS: The gut microbiome can influence the production and activity of immune cells and molecules that help to maintain the integrity of the intestinal barrier and prevent inflammation. Gut microbiota modulates the anti-cancer immune response. The gut microbiota can influence the function of immune cells, like T cells, that recognize and eliminate cancer cells. Gut microbiota can affect various aspects of cancer progression and the efficacy of various anti-cancer treatments. RESULTS: Gut microbiota provide promise as a potential biomarker to identify the effect of immunotherapy and as a target for modulation to improve the efficacy of immunotherapy in CRC treatment. CONCLUSION: The potential synergistic effect between the gut microbiome and anti-cancer treatment modalities provides an interest in developing strategies to modulate the gut microbiome to improve the efficacy of anti-cancer treatment.

This review focuses on the gut microbiome in the development and regulation of the host immune system. Gut microbiota provides potential biomarkers to identify the effect of immunotherapy and as a target for modulation of immunotherapy in the treatment of CRC. This provides potential synergistic effects between the gut microbiome and anti-cancer treatment modalities.

Heartfelt living: Deciphering the link between lifestyle choices and cardiovascular vitality.

Cardiovascular diseases (CVDs) are still leading to a significant number of deaths worldwide despite the remarkable advancements in medical technology and pharmacology. Managing patients with established CVDs is a challenge for healthcare providers as it requires reducing the chances of recurring cardiovascular events. On the other hand, changing one's way of life can also significantly impact this area, reducing the likelihood of cardiovascular disease and death through their unique advantages. Consequently, it is advisable for healthcare providers to regularly advise their patients with coronary issues to participate in organized physical exercise and improve their overall physical activity. Additionally, patients should adhere to a diet that promotes heart health, cease smoking, avoid exposure to secondhand smoke, and address any psychosocial stressors that may heighten the risk of cardiovascular problems. These lifestyle therapies, whether used alongside drug therapy or on their own in patients who may have difficulty tolerating medications, face financial barriers, or experience ineffectiveness, can substantially reduce cardiovascular mortality and the likelihood of recurring cardiac events. Despite the considerable advancements in creating interventions, it is still necessary to determine the optimal intensity, duration, and delivery method for these interventions. Furthermore, it is crucial to carry out further investigations incorporating extended monitoring and assessment of clinical outcomes to get a more comprehensive comprehension of the efficacy of these therapies. Presenting the findings within the framework of "lifestyle medicine," this review seeks to offer a thorough synopsis of the most recent scientific investigations into the potential of behavioral modifications to lower cardiovascular disease risk.

Beyond the silence: A comprehensive exploration of long non-coding RNAs as genetic whispers and their essential regulatory functions in cardiovascular disorders.

Long non-coding RNAs (lncRNAs) are RNA molecules that regulate gene expression at several levels, including transcriptional, post-transcriptional, and translational. They have a length of more than 200 nucleotides and cannot code. Many human diseases have been linked to aberrant lncRNA expression, highlighting the need for a better knowledge of disease etiology to drive improvements in diagnostic, prognostic, and therapeutic methods. Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide. LncRNAs play an essential role in the complex process of heart formation, and their abnormalities have been associated with several CVDs. This Review article looks at the roles and relationships of long non-coding RNAs (lncRNAs) in a wide range of CVDs, such as heart failure, myocardial infarction, atherosclerosis, and cardiac hypertrophy. In addition, the review delves into the possible uses of lncRNAs in diagnostics, prognosis, and clinical treatments of cardiovascular diseases. Additionally, it considers the field's future prospects while examining how lncRNAs might be altered and its clinical applications.

Single-cell RNA Sequencing (scRNA-seq): Advances and Challenges for Cardiovascular Diseases (CVDs).

Implementing Single-cell RNA sequencing (scRNA-seq) has significantly enhanced our comprehension of cardiovascular diseases (CVDs), providing new opportunities to strengthen the prevention of CVDs progression. Cardiovascular diseases continue to be the primary cause of death worldwide. Improving treatment strategies and patient risk assessment requires a deeper understanding of the fundamental mechanisms underlying these disorders. The advanced and widespread use of Single-cell RNA sequencing enables a comprehensive investigation of the complex cellular makeup of the heart, surpassing essential descriptive aspects. This enhances our understanding of disease causes and directs functional research. The significant advancement in understanding cellular phenotypes has enhanced the study of fundamental cardiovascular science. scRNA-seq enables the identification of discrete cellular subgroups, unveiling previously unknown cell types in the heart and vascular systems that may have relevance to different disease pathologies. Moreover, scRNA-seq has revealed significant heterogeneity in phenotypes among distinct cell subtypes. Finally, we will examine current and upcoming scRNA-seq studies about various aspects of the cardiovascular system, assessing their potential impact on our understanding of the cardiovascular system and offering insight into how these technologies may revolutionise the diagnosis and treatment of cardiac conditions.

Beyond the beat: A pioneering investigation into exercise modalities for alleviating diabetic cardiomyopathy and enhancing cardiac health.

Patients with preexisting cardiovascular disease or those at high risk for developing the condition are often offered exercise as a form of therapy. Patients with cancer who are at an increased risk for cardiovascular issues are increasingly encouraged to participate in exercise-based, interdisciplinary programs due to the positive correlation between these interventions and clinical outcomes following myocardial infarction. Diabetic cardiomyopathy (DC) is a cardiac disorder that arises due to disruptions in the homeostasis of individuals with diabetes. One of the primary reasons for mortality in individuals with diabetes is the presence of cardiac structural damage and functional abnormalities, which are the primary pathological features of DC. The aetiology of dilated cardiomyopathy is multifaceted and encompasses a range of processes, including metabolic abnormalities, impaired mitochondrial function, dysregulation of calcium ion homeostasis, excessive cardiomyocyte death, and fibrosis. In recent years, many empirical investigations have demonstrated that exercise training substantially impacts the prevention and management of diabetes. Exercise has been found to positively impact the recovery of diabetes and improve several metabolic problem characteristics associated with DC. One potential benefit of exercise is its ability to increase systolic activity, which can enhance cardiometabolic and facilitate the repair of structural damage to the heart caused by DC, leading to a direct improvement in cardiac health. In contrast, exercise has the potential to indirectly mitigate the pathological progression of DC through its ability to decrease circulating levels of sugar and fat while concurrently enhancing insulin sensitivity. A more comprehensive understanding of the molecular mechanism via exercise facilitates the restoration of DC disease must be understood. Our goal in this review was to provide helpful information and clues for developing new therapeutic techniques for motion alleviation DC by examining the molecular mechanisms involved.

Enhanced payload volume in the least significant bits image steganography using hash function.

The art of message masking is called steganography. Steganography keeps communication from being seen by any other person. In the domain of information concealment within images, numerous steganographic techniques exist. Digital photos stand out as prime candidates due to their widespread availability. This study seeks to develop a secure, high-capacity communication system that ensures private interaction while safeguarding information from the broader context. This study used the four least significant bits for steganography to hide the message in a secure way using a hash function. Before steganography, the message is encrypted using one of the encryption techniques: Caesar cipher or Vigenère cipher. By altering only the least significant bits (LSBs), the changes between the original and stego images remain invisible to the human eye. The proposed method excels in secret data capacity, featuring a high peak signal-to-noise ratio (PSNR) and low mean square error (MSE). This approach offers significant payload capacity and dual-layer security (encryption and steganography).

Methyl-CpG-Binding Protein 2 Emerges as a Central Player in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders.

MECP2 and its product methyl-CpG binding protein 2 (MeCP2) are associated with multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD), which are inflammatory, autoimmune, and demyelinating disorders of the central nervous system (CNS). However, the mechanisms and pathways regulated by MeCP2 in immune activation in favor of MS and NMOSD are not fully understood. We summarize findings that use the binding properties of MeCP2 to identify its targets, particularly the genes recognized by MeCP2 and associated with several neurological disorders. MeCP2 regulates gene expression in neurons, immune cells and during development by modulating various mechanisms and pathways. Dysregulation of the MeCP2 signaling pathway has been associated with several disorders, including neurological and autoimmune diseases. A thorough understanding of the molecular mechanisms underlying MeCP2 function can provide new therapeutic strategies for these conditions. The nervous system is the primary system affected in MeCP2-associated disorders, and other systems may also contribute to MeCP2 action through its target genes. MeCP2 signaling pathways provide promise as potential therapeutic targets in progressive MS and NMOSD. MeCP2 not only increases susceptibility and induces anti-inflammatory responses in immune sites but also leads to a chronic increase in pro-inflammatory cytokines gene expression (IFN-γ, TNF-α, and IL-1ß) and downregulates the genes involved in immune regulation (IL-10, FoxP3, and CX3CR1). MeCP2 may modulate similar mechanisms in different pathologies and suggest that treatments for MS and NMOSD disorders may be effective in treating related disorders. MeCP2 regulates gene expression in MS and NMOSD. However, dysregulation of the MeCP2 signaling pathway is implicated in these disorders. MeCP2 plays a role as a therapeutic target for MS and NMOSD and provides pathways and mechanisms that are modulated by MeCP2 in the regulation of gene expression.

Vegetation-environment interactions: plant species distribution and community assembly in mixed coniferous forests of Northwestern Himalayas.

One of the main goals of ecological studies is to disentangle the dynamics that underlie the spatiotemporal distribution of biodiversity and further functions of the ecosystem. However, due to many ecological and geopolitical reasons, many remote areas with high plant species diversity have not been assessed using newly based analytical approaches for vegetation characterization. Here, we classified and characterized different vegetation types (i.e., major plant communities) based on indicator species and on the influence of different environmental gradients in the Himalayan mixed coniferous forest, Pakistan. For that, we addressed the following questions: Does the vegetation composition of the Himalayan mixed coniferous forest correlate with climatic, topographic, geographic, and edaphic variables? Is it possible to identify plant communities through indicator species in relation to environmental gradients using multivariate approaches? Can this multivariate be helpful for conservation planning? During four consecutive years we assessed the vegetation composition and environmental variables (21 variables divided in geographic, climatic, topographic, and edaphic groups) of 156 50 m-trasects between an elevation of 2000-4000 m. Using newly based analytical approaches for community characterization, we found a total of 218 plant species clustered into four plant communities with the influence of environmental gradients. The highest index of similarity was recorded between Pinus-Cedrus-Viburnum (PCV) and Viburnum-Pinus-Abies (VPA) communities, and the highest index of dissimilarity was recorded between PCV and Abies-Juniperus-Picea (AJP) communities. Among these four communities, highest number of plant species (156 species) was recorded in PCV, maximum alpha diversity (H' = 3.68) was reported in VPA, highest Simpson index (0.961) and Pielou's evenness (0.862) were reported in VPA and AJP. The edaphic gradients (i.e., organic matter, phosphorous, pH and soil texture) and climatic factors (temperature, humidity) were the strongest environmental gradients that were responsible for structuring and hosting the diverse plant communities in mixed coniferous forest. Finally, the Himalayan mixed coniferous structure is more influenced by the spatial turnover beta-diversity process (ßsim) than by the species loss (nestedness-resultant, ßsne). Our analysis of the vegetation structure along the environmental gradient in the Himalayan mixed coniferous forest supported by sophisticated analytical approaches reveled indicator species groups, which are associated to specific microclimatic zones (i.e., vegetation communities). Within this focus, we side with the view that these results can support conservation planning and management for similar and different areas providing mitigating and preventive measures to reduce potential negative impacts, such as anthropic and climatic.

Variants in EFCAB7 underlie nonsyndromic postaxial polydactyly.

Polydactyly is the most common limb malformation that occurs in 1.6-10.6 per one thousand live births, with incidence varying with ancestry. The underlying gene has been identified for many of the ~100 syndromes that include polydactyly. While for the more common form, nonsydromic polydactyly, eleven candidate genes have been reported. We investigated the underlying genetic cause of autosomal recessive nonsyndromic postaxial polydactyly in four consanguineous Pakistani families. Some family members with postaxial polydactyly also present with syndactyly, camptodactyly, or clinodactyly. Analysis of the exome sequence data revealed two novel homozygous frameshift deletions in EFCAB7: [c.830delG;p.(Gly277Valfs*5)]; in three families and [c.1350_1351delGA;p.(Asn451Phefs*2)] in one family. Sanger sequencing confirmed that these variants segregated with postaxial polydactyly, i.e., family members with postaxial polydactyly were found to be homozygous while unaffected members were heterozygous or wild type. EFCAB7 displays expressions in the skeletal muscle and on the cellular level in cilia. IQCE-EFCAB7 and EVC-EVC2 are part of the heterotetramer EvC complex, which is a positive regulator of the Hedgehog (Hh) pathway, that plays a key role in limb formation. Depletion of either EFCAB7 or IQCE inhibits induction of Gli1, a direct Hh target gene. Variants in IQCE and GLI1 have been shown to cause nonsyndromic postaxial polydactyly, while variants in EVC and EVC2 underlie Ellis van Creveld and Weyers syndromes, which include postaxial polydactyly as a phenotype. This is the first report of the involvement of EFCAB7 in human disease etiology.

A variant in the LDL receptor-related protein encoding gene LRP4 underlying polydactyly and phalangeal synostosis in a family of Pakistani origin.

A family of Pakistani origin, segregating polydactyly, and phalangeal synostosis in an autosomal dominant manner, has been investigated and presented in the present report. Whole-exome sequencing (WES), followed by segregation analysis using Sanger sequencing, revealed a heterozygous missense variant [c.G1696A, p.(Gly566Ser)] in the LRP4 gene located on human chromosome 11p11.2. Homology protein modeling revealed the mutant Ser566 generated new interactions with at least four other amino acids and disrupted protein folding and function. Our findings demonstrated the first direct evidence of involvement of LRP4 in causing polydactyly and phalangeal synostosis in the same family. This study highlighted the importance of inclusion of LRP4 gene in screening individuals presenting polydactyly in hands and feet, and phalangeal synostosis in the same family.

Identification of Drug Targets and Their Inhibitors in Yersinia pestis Strain 91001 through Subtractive Genomics, Machine Learning, and MD Simulation Approaches.

Yersinia pestis, the causative agent of plague, is a Gram-negative bacterium. If the plague is not properly treated it can cause rapid death of the host. Bubonic, pneumonic, and septicemic are the three types of plague described. Bubonic plague can progress to septicemic plague, if not diagnosed and treated on time. The mortality rate of pneumonic and septicemic plague is quite high. The symptom-defining disease is the bubo, which is a painful lymph node swelling. Almost 50% of bubonic plague leads to sepsis and death if not treated immediately with antibiotics. The host immune response is slow as compared to other bacterial infections. Clinical isolates of Yersinia pestis revealed resistance to many antibiotics such as tetracycline, spectinomycin, kanamycin, streptomycin, minocycline, chloramphenicol, and sulfonamides. Drug discovery is a time-consuming process. It always takes ten to fifteen years to bring a single drug to the market. In this regard, in silico subtractive proteomics is an accurate, rapid, and cost-effective approach for the discovery of drug targets. An ideal drug target must be essential to the pathogen's survival and must be absent in the host. Machine learning approaches are more accurate as compared to traditional virtual screening. In this study, k-nearest neighbor (kNN) and support vector machine (SVM) were used to predict the active hits against the beta-ketoacyl-ACP synthase III drug target predicted by the subtractive genomics approach. Among the 1012 compounds of the South African Natural Products database, 11 hits were predicted as active. Further, the active hits were docked against the active site of beta-ketoacyl-ACP synthase III. Out of the total 11 active hits, the 3 lowest docking score hits that showed strong interaction with the drug target were shortlisted along with the standard drug and were simulated for 100 ns. The MD simulation revealed that all the shortlisted compounds display stable behavior and the compounds formed stable complexes with the drug target. These compounds may have the potential to inhibit the beta-ketoacyl-ACP synthase III drug target and can help to combat Yersinia pestis-related infections. The dataset and the source codes are freely available on GitHub.

An efficient optimizer for the 0/1 knapsack problem using group counseling.

The field of optimization is concerned with determining the optimal solution to a problem. It refers to the mathematical loss or gain of a given objective function. Optimization must reduce the given problem's losses and disadvantages while maximizing its earnings and benefits. We all want optimal or, at the very least, suboptimal answers because we all want to live a better life. Group counseling optimizer (GCO) is an emerging evolutionary algorithm that simulates the human behavior of counseling within a group for solving problems. GCO has been successfully applied to single and multi-objective optimization problems. The 0/1 knapsack problem is also a combinatorial problem in which we can select an item entirely or drop it to fill a knapsack so that the total weight of selected items is less than or equal to the knapsack size and the value of all items is as significant as possible. Dynamic programming solves the 0/1 knapsack problem optimally, but the time complexity of dynamic programming is O(n3). In this article, we provide a feature analysis of GCO parameters and use it to solve the 0/1 knapsack problem (KP) using GCO. The results show that the GCO-based approach efficiently solves the 0/1 knapsack problem; therefore, it is a viable alternative to solving the 0/1 knapsack problem.

Abstractive text summarization of low-resourced languages using deep learning.

Background: Humans must be able to cope with the huge amounts of information produced by the information technology revolution. As a result, automatic text summarization is being employed in a range of industries to assist individuals in identifying the most important information. For text summarization, two approaches are mainly considered: text summarization by the extractive and abstractive methods. The extractive summarisation approach selects chunks of sentences like source documents, while the abstractive approach can generate a summary based on mined keywords. For low-resourced languages, e.g., Urdu, extractive summarization uses various models and algorithms. However, the study of abstractive summarization in Urdu is still a challenging task. Because there are so many literary works in Urdu, producing abstractive summaries demands extensive research. Methodology: This article proposed a deep learning model for the Urdu language by using the Urdu 1 Million news dataset and compared its performance with the two widely used methods based on machine learning, such as support vector machine (SVM) and logistic regression (LR). The results show that the suggested deep learning model performs better than the other two approaches. The summaries produced by extractive summaries are processed using the encoder-decoder paradigm to create an abstractive summary. Results: With the help of Urdu language specialists, the system-generated summaries were validated, showing the proposed model's improvement and accuracy.

Different Dimensionalities, Morphological Advancements and Engineering of g-C3 N4 -Based Nanomaterials for Energy Conversion and Storage.

Graphitic carbon nitride (g-C3 N4 ) has gained tremendous interest in the sector of power transformation and retention, because of its distinctive stacked composition, adjustable electronic structure, metal-free feature, superior thermodynamic durability, and simple availability. Furthermore, the restricted illumination and extensive recombination of photoexcitation electrons have inhibited the photocatalytic performance of pure g-C3 N4 . The dimensions of g-C3 N4 may impact the field of electronics confinement; as a consequence, g-C3 N4 with varying dimensions shows unique features, making it appropriate for a number of fascinating uses. Even if there are several evaluations emphasizing on the fabrication methods and deployments of g-C3 N4 , there is certainly an insufficiency of a full overview, that exhaustively depicts the synthesis and composition of diverse aspects of g-C3 N4 . Consequently, from the standpoint of numerical simulations and experimentation, several legitimate methodologies were employed to deliberately develop the photocatalyst and improve the optimal result, including elements loading, defects designing, morphological adjustment, and semiconductors interfacing. Herein, this evaluation initially discusses different dimensions, the physicochemical features, modifications and interfaces design development of g-C3 N4 . Emphasis is given to the practical design and development of g-C3 N4 for the various power transformation and inventory applications, such as photocatalytic H2 evolution, photoreduction of CO2 source, electrocatalytic H2 evolution, O2 evolution, O2 reduction, alkali-metal battery cells, lithium-ion batteries, lithium-sulfur batteries, and metal-air batteries. Ultimately, the current challenges and potential of g-C3 N4 for fuel transformation and retention activities are explored.