Cluster Region Research Articles

Genetic variations in human opsin genetics: Understanding color vision phenotypes and defects

Purpose: The aim of this study was to analyze human opsin genes, OPN1LW and OPN1MW, for single nucleotide polymorphisms (SNP) and structural variants (SV) impacting color vision in subjects diagnosed with color vision deficiency.Methods: Nineteen subjects underwent anomaloscope examination to diagnose color vision deficiency phenotypes (dichromatic: protanopia and deuteranopia). First, a previously published method of long range‐PCR and sequencing was performed to identify variations in OPN1LW, OPN1MW, and OPN1SW. In the case of discrepancy, ultra‐long nanopore sequencing was utilized to identify possible SVs.Results: The long range‐PCR and sequencing genetically validated the color vision diagnosis for 17 of the 19 individuals. For two individuals the genetic and functional diagnoses conflicted. Ultra‐long nanopore sequencing of these two revealed possible rearrangements in the opsin gene cluster that could affect the color vision and explain the conflicting results based on the long‐PCR method.Conclusions: The large size of the human opsin gene cluster and the high degree of sequence homology between OPN1LW and OPN1MW genes have been a challenge for genetic studies of color vision deficiencies. The development of ultra‐long nanopore sequencing technology allows for a more comprehensive genetic analysis of this region, especially for the detection of pathogenic SVs. In this study, we were able to identify possible SVs underlying color vision deficiency in cases that were missed by the long range‐PCR. However, alignment of the ultra‐long sequences to the reference genome at the variable opsin gene cluster region remains a challenge for the data analysis.

Genetic variations in human opsin genetics: Understanding color vision phenotypes and defects

Purpose: The aim of this study was to analyze human opsin genes, OPN1LW and OPN1MW, for single nucleotide polymorphisms (SNP) and structural variants (SV) impacting color vision in subjects diagnosed with color vision deficiency.Methods: Nineteen subjects underwent anomaloscope examination to diagnose color vision deficiency phenotypes (dichromatic: protanopia and deuteranopia). First, a previously published method of long range‐PCR and sequencing was performed to identify variations in OPN1LW, OPN1MW, and OPN1SW. In the case of discrepancy, ultra‐long nanopore sequencing was utilized to identify possible SVs.Results: The long range‐PCR and sequencing genetically validated the color vision diagnosis for 17 of the 19 individuals. For two individuals the genetic and functional diagnoses conflicted. Ultra‐long nanopore sequencing of these two revealed possible rearrangements in the opsin gene cluster that could affect the color vision and explain the conflicting results based on the long‐PCR method.Conclusions: The large size of the human opsin gene cluster and the high degree of sequence homology between OPN1LW and OPN1MW genes have been a challenge for genetic studies of color vision deficiencies. The development of ultra‐long nanopore sequencing technology allows for a more comprehensive genetic analysis of this region, especially for the detection of pathogenic SVs. In this study, we were able to identify possible SVs underlying color vision deficiency in cases that were missed by the long range‐PCR. However, alignment of the ultra‐long sequences to the reference genome at the variable opsin gene cluster region remains a challenge for the data analysis.

Analysis of Regional Economic Disparities and Voter Turnout in the 2024 Elections in Korea and Mexico Using Big Data

This study examines the impact of regional economic disparities on voter turnout in South Korea and Mexico using machine learning and statistical analysis. A country comparison analysis showed that economic centers with high GRDP had lower voter turnout in both countries. K-means clustering identified three regional clusters, revealing a trend where regions with higher economic growth or economic hardship tended to have lower participation rates. In South Korea, multiple regression analysis indicated that the home sales index had the largest influence on turnout, while income and wealth had smaller effects. Economic expectations from the Consumer Sentiment Survey were insignificant. In Mexico, analyses of business activity and workforce percentages showed that closed businesses had a slight negative effect on turnout, but overall, economic variables did not significantly impact participation. This study provides key insights for companies operating in South Korea and Mexico, emphasizing the importance of aligning market entry strategies with regional socioeconomic and political dynamics. Businesses targeting economically prosperous areas must address potential political disengagement and policy unpredictability, while those in regions with moderate economic activity may benefit from stronger community engagement. Additionally, firms in economically challenged areas should prioritize CSR initiatives to address inequality and foster sustainable operations.

Implementasi Business Intelligence Menggunakan ETL dan K-MEANS untuk Visualisasi Data Bencana Alam di Jawa Barat

In addition to its abundant natural wealth, West Java also harbors a high potential for disasters. The increasing frequency of natural disasters in recent years, such as earthquakes, landslides, and floods, has caused significant losses to the community. Climate change and environmentally unfriendly human activities are the main factors causing these disasters. Therefore, mitigation and preparedness efforts are key in facing future disaster threats. Business Intelligence can be used to process data and provide relevant information, which is a part of information technology. The purpose of this research is to visualize areas affected by natural disasters in West Java Province by implementing Business Intelligence. The method of this research is obtained in the form of a dataset sourced from the West Java Provincial Community and Village Empowerment Office, obtained through https://opendata.jabarprov.go.id/id for the period from 2020 to 2022. In this research, ETL (Extract, Transform, Load) is used to handle data, including extraction (Extract), transformation (Transform), and loading (Load), as well as K-Means calculations to cluster regions based on clusters. The result of this research is in the form of a dashboard report with the help of Google Data Studio, displaying data visualization results for the West Java region affected by natural disasters. Based on the visualization results, the areas in West Java Province with a high risk of natural disasters that fall into the first cluster in 2020 had 2 regions, in 2021 had 4 regions, and in 2022 had only 1 region.

Regional clustering of FEC enterprises to strengthen the country's economic security

Regional clustering of FEC enterprises to strengthen the country's economic security

Amino acid substitution patterns in the <i>E6</i> and <i>E7</i> Proteins of HPV type 16: Phylogeography and Evolution

The E6 and E7 proteins of human papillomavirus (HPV) play a key role in the oncogenesis of papillomavirus infection. Data on the variability of these proteins are limited, and the factors affecting their variability are poorly understood. We analyzed the variability of the currently known sequences of HPV type 16 (HPV16) E6 and E7 proteins, taking into account their geographic origin and year of sample collection, as well as the direction of their evolution in major geographic regions of the world. All sequences belonging to HPV16 genome fragments encoding E6 and E7 oncoproteins were downloaded from the NCBI GenBank database on October 6, 2022. Samples were filtered according to the following parameters: the sequence includes at least one of the two whole open reading frames, the collection date and the country of origin are known. A total of 3,651 full-genome nucleotide sequences encoding the E6 protein and 4,578 full-genome nucleotide sequences encoding the E7 protein were sampled. The nucleotide sequences obtained after sampling and alignment were converted to amino acid sequences and analyzed using MEGA11, R, RStudio, Jmodeltest 2.1.20, BEAST v1.10.4, Fastcov, and Biostrings software. The highest variability in E6 protein structure was recorded at positions 17, 21, 32, 85, and 90, while in E7, positions 28, 29, 51, and 77 were the most variable. The samples were divided geographically into 5 heterogeneous groups: African, European, American, Southwest and South Asia and Southeast Asia. Unique amino acid substitutions (AA-substitutions) in the E6/E7 proteins of HPV16, presumably characteristic of certain ethnic groups, were identified for a number of countries. They are mainly localized in sites of known B- and T-cell epitopes and relatively rarely in structural and functional domains. The revealed differences in AA-substitutions in different ethnic groups and their colocalization with clusters of B- and T-cell epitopes suggest their possible relationship with the geographical distribution of alleles and haplotypes of the major histocompatibility complex (HLA). This may lead to the recognition of a different set of B- and T-cell epitopes of the virus, resulting in regional differences in the direction of epitope drift. Phylogenetic analysis of the nucleotide sequences encoding the E6 protein of HPV16 revealed a common ancestor, confirmed regional clustering of the E6 protein gene sequences by the set of the most common AA-substitutions, and identified cases of reversion of individual AA-substitutions when the virus distribution region changed. For the E7 protein, a similar analysis was not possible due to high sequence homology. Covariance analysis of the pooled sample revealed that there was no relationship between amino acid residues in the E6 protein, in the E7 protein, and between E6 and E7. Data obtained are important for the development of therapeutic vaccines against HPV of high carcinogenic risk.

Взаимосвязь уровня социально-экономического развития и инновационно-инвестиционного потенциала региона

In the context of the transition of the Russian Federation to innovation-oriented economic growth, the importance of the innovation and investment potential of meso-level socio-economic systems is increasing. The inconsistency of the activities of economic agents in the context of the transformation of the economic model leads to the fact that regional policy faces a number of challenges that cause a decrease in the effectiveness of strategic development. It is assumed that determining the priorities of the spatial and sectoral structure in the development of socio-economic development Strategies allows regions to effectively adapt to environmental conditions and form a competitive innovation infra-structure under the influence of a favorable investment climate. The purpose of this work is to study the regularity of the region's position in the ratings from the presence of priorities of the spatial and sectoral structure in the implementa-tion of the Strategy of socio-economic development and strengthening of innovation and investment potential. The paper analyzed the regional distribution according to Russian ratings with further research of socio-economic develop-ment Strategies and a general assessment of the factors studied, which made it possible to identify the importance of the interdependence of priority areas of the spatial and sectoral structure of the region with the Strategy of socio-economic development and innovation and investment potential. The author's model of the regional innovation system is proposed, which allows to gradually determine the subsystems of the implementation of regional investment and innovation policy, as well as to assess the possibilities of their dynamic interaction, ensuring the continuous circulation of knowledge, investment flows and human capital. The innovation and investment potential as a result of the coordi-nation of the elements of the regional innovation system represents a triad of interaction between the system of creation, dissemination and application of knowledge. The communicative interaction between science, education and business leads to the formation of regional innovation clusters, which are the highest manifestation of the level of development of the innovation and investment potential of the socio-economic system (region/subject of the Russian Federation).

Structural-phase transformations and crystallographic texture in commercial Ti–6Al–4V alloy with globular morphology of α-phase grains: the rolling plane

The commercial Ti–6Al–4V alloy was obtained in an almost single-phase state, formed by finely dispersed globular α-grains with an average size of 12 μm, using thermomechanical processing, including hot rolling. The microtexture and structure of the alloy were studied using X-ray diffractometry and transmission and scanning electron microscopy, including orientation microscopy. It is found that for α-grains the Burgers orientation relationships are satisfied, and twin orientations are ensured in the rolling plane. A significant scattering of the crystallographic orientations of α-grains relative to each other (up to 10°–15°) is established for each group of close Burgers orientations as a result of plastic deformation by rolling at high temperatures. Clusters of microtexture regions in the layered microstructure of grains and the formation mechanisms and mutual crystallographic misorientations of microtexture regions and grains in the alloy have been identified.

Genetic diversity and variation in chronic myeloid leukemia patients of Indian origin- Implications for treatment response and prognosis

Chronic myeloid leukemia (CML) is a prevalent blood malignancy characterized by the breakpoint cluster region - abelson tyrosine kinase gene translocation (BCR-ABL1) fusion gene. In India, CML accounts for a significant portion of adult leukemias, with a notable male preponderance and an increasing trend in young adult patients. Most patients present in the chronic phase, and the Sokal/European treatment and outcome study score (EUTOS)/Hasford scoring systems may be used for risk stratification. The advent of imatinib revolutionized CML treatment, making it more accessible, although challenges such as intolerance and treatment failure persist. Cytogenetic analysis is essential for diagnosis and monitoring, with molecular assessments indicating treatment response. Compliance plays a crucial role in achieving optimal outcomes, with non-adherence associated with poorer prognosis. Mutational analysis aids in treatment decisions for patients with suboptimal response to tyrosine kinase inhibitors, revealing resistance patterns. Toxicity profiles resemble Western data, with anemia being the most common hematological toxicity. Despite limitations in resources and late presentations, Indian CML outcomes mirror Western standards, highlighting the importance of standardized cytogenetic testing for improved clinical outcomes.

Low Injection Rate of Cosmic-Ray Protons in the Turbulent Reacceleration Model of Radio Halos in Galaxy Clusters

A giant radio halo (RH) is a diffuse synchrotron emission observed on the scale of megaparsecs, typically found in the central region of merging galaxy clusters. Its large size and steep spectrum suggest that it originates from the reenergization of an aged population of cosmic-ray electrons (CREs), while the secondary leptons produced in the pp hadronic collision of cosmic-ray protons (CRPs) may contribute to the emission. In this study, we investigate the reacceleration model including both primary and secondary CREs, assuming that the primary cosmic rays (CRs) originate from internal galaxies. In our new method, we follow the cosmological evolution of each cluster and calculate the energy spectra and 1D spatial distributions of CRs. The primary CRE model with a ∼3 Gyr duration of reacceleration successfully reproduces the statistical properties of the RHs observed in the recent LOFAR survey, as well as the spectrum and profile of the Coma cluster. The gamma-ray and neutrino emissions produced by reaccelerated CRPs are consistent with the upper limits. However, if the CRP injection rate is high and the secondary CREs become significant, the model with the required ∼3 Gyr reacceleration overproduces the number of RHs. The limit on the CRP injection rate, L p ≲ 1041 erg s−1, is significantly lower than that expected from the early starburst activity or jets from active galactic nuclei. This discrepancy requires a revision of either the model of CR supply from galaxies or the turbulent reacceleration model.

A Multi-case Study of Green Port-adjacent Industrial Cluster Development Based on Grounded Theory

This paper adopts a multi-case analysis approach, selecting the port-adjacent industrial clusters in Ningbo, China, Rotterdam, Netherlands, and Tokyo Bay, Japan, as exemplary cases for study. It collects multi-source data and information from academic literature, official channels, news reports, and social media. By applying the three-level coding process of Grounded Theory, it delves into successful practices of these cases in constructing and developing green port-adjacent industrial clusters, and extracts the valuable experiences of them. Based on this, a series of strategic conclusions aimed at promoting the development of green port-adjacent industrial clusters are summarized, providing useful references and insights for the formation and development pathways of port-adjacent industrial clusters in other regions.

The geographies and geopolitics of industrial policy: Designing a data-driven UK semiconductor strategy

Industrial policy is witnessing a global resurgence. We propose that well-designed industrial policy must consider an industry’s regional structures, global linkages, and (variegated) exposures to geopolitical dynamics. In 2023, the UK government published a National Semiconductor Strategy. The National Semiconductor Strategy aims to grow this high-value sector, mitigate supply chain disruptions and protect national security. However, the strategy relies on an incomplete portrait of the industry’s regional geography, global integration and geopolitical exposures. Using newly available commercial data, this commentary examines 61 leading UK semiconductor firms to offer a far more comprehensive mapping of the UK’s semiconductor ecosystem than the National Semiconductor Strategy. Our analysis reveals overlooked aspects of the UK semiconductor industry. The Midlands and North West emerge as potentially under-recognised semiconductor hubs, with a significant workforce and revenue share. Heavy reliance on US suppliers, customers and investors creates vulnerabilities not addressed in the current strategy. Strong European ties exist, but Brexit-related trade barriers may harm UK firms. Last, we detect a subtle, though probably uncoordinated, pattern of Chinese investment in the sector that could expose UK firms to growing US-China tensions. We recommend that the new UK government take four steps. First, revise the National Semiconductor Strategy based on an up-to-date and systematic survey of the industry’s global linkages. Second, it will enhance its supply chain resilience strategy to address geopolitical risk and Brexit-related frictions. Third, track foreign investment patterns in high technology sectors especially regarding incremental changes in Chinese ownership. Fourth, to do so on the basis of close attention to regional clustering dynamics.

ANALYSIS OF INTELLECTUAL AND DIGITAL CAPITAL OF RUSSIAN REGIONS

The widespread use of digital technologies stimulates the transformation and modernization of many traditional sectors of the economy at the regional level. However, the effective use of digital technologies is impossible without the appropriate knowledge, skills and experience, which is the subject of this study - intellectual and digital capital. In addition, despite the importance and relevance of the study of digital technologies and intellectual and digital capital, there are no methods for its quantitative assessment in modern scientific literature. Thus, the purpose of the study is to develop a quantitative method for assessing intellectual and digital capital at the regional level. As a result of the study, a methodology for the quantitative analysis of intellectual and digital capital is proposed - the index of intellectual and digital capital, consisting of two sub-indices: DKE - index of digital knowledge and experience; DTA - index of digital tangible assets and rights to the results of intellectual activity that contribute to the digital development of society. Clustering of Russian regions in accordance with the values of the DKE and DTA indices has been developed. The results of the study can be applied in public policy. Based on the role of the digital economy in ensuring sustainable development in the Russian Federation, this study focused on the analysis of the development of digital technologies and digital knowledge and experience. The implemented clustering of Russian regions made it possible to identify territories in which the relationship between digital technologies and digital knowledge determines both highly effective and low-effective digitalization of the socio-economic development of society.

Molecular docking and ADMET profiling of Carbazole-rhodanine hybrid as anticancer agent

Drug resistance and lack of specificity of currently available chemotherapeutics for cancer cells contribute to the failure of cancer chemotherapy. This highlights the pressing need to develop novel anticancer agents. This research aims to investigate the inhibiting potential of Carbazole and rhodanine derivatives against Human papillomaviruses (HPVs) and Breakpoint Cluster Region (BCR), with Abelson murine leukemia (ABL) tyrosine kinase to manage human cervical cancer and human chronic myeloid leukemia (CML), respectively. Some carbazole-rhodanine hybrids were evaluated in silico against human cervical cancer (Hela) and human CML (K562) cells. In this study, Molecular docking was used to determine binding affinity, bonding, and nonbonding interaction between the studied compounds and the target. Additionally, in-silico ADMET (adsorption, distribution, metabolism, excretion, and toxicity) screening was performed to explore the bioavailability, pharmacokinetic properties, and toxicity of the carbazole-rhodanine hybrids. The structure of the compounds was also discussed relative to their bioactivity. The molecular docking revealed that the test compounds except D, E, and L demonstrated better binding affinity, hence better inhibition efficiency towards Hela and K562 cell lines than the reference drug (etoposide). Compound G with a cyano substituent showed the highest binding affinity with the two receptors used, with a binding energy of -7.9 kcal mol-1 against hela (6HKS) and -10.0 against K562 (5HU9). This was in accordance with the experimental result. The SAR illustrated that a strong electron-withdrawing substituent attached to the para-position of the phenyl ring increased the activity. The ADMET profiling showed that compounds E, G, and J had superior drug-likeness, pharmacokinetic, and toxicity properties. Based on the results, compound G may be a good candidate to be developed further into a therapeutic agent to treat chronic myeloid leukemia and cervical cancer.

A new condition for Root Clustering in PMI regions

A new condition for Root Clustering in PMI regions

Coupling Coordination Analysis between Total Factor Productivity and Digital Economy in China’s Agriculture

This study aims to systematically analyze the coupling and coordinated development between the digital economy (DE) and total factor productivity (TFP) in China’s agricultural sector, focusing on their impact on regional agricultural advancement. Using a comprehensive dataset from 31 Chinese provinces covering the period from 2014 to 2021, we apply the EBM model, entropy weight method, and coupling coordination degree model to assess TFP-DE interactions. To capture spatial-temporal dynamics and regional disparities, we employ kernel density estimation, Moran’s I index, the Dagum Gini coefficient, and an obstacle degree model. The findings reveal an initial phase of “multipolarization” in TFP-DE coordination, which gradually stabilizes towards preliminary coordination levels. Despite this progress, significant regional imbalances persist, particularly in central and western provinces where “low-low” clusters dominate, in contrast to the “high-high” clusters in eastern regions. While disparities in coordination have narrowed in eastern areas, they continue to widen across central and western regions. The primary obstacles have shifted from foundational infrastructure to challenges directly associated with DE and TFP. This study underscores the necessity of region-specific policies to address these disparities, particularly in underdeveloped areas, to enhance agricultural productivity through digital integration. The findings provide a strategic foundation for policymakers to foster balanced and sustainable growth, contributing to China’s broader goals for agricultural modernization.

Surface-Based Morphometry Findings Reveal Structural Alterations of the Brain in Meige Syndrome.

To compare structural alterations in the brains of Meige syndrome (MS) patients with those of healthy controls (HCs) by using surface-based morphometry (SBM) and compare structural differences between the brains of MS patients with sleep disorders and those of MS patients without sleep disorders. We investigated cortical surface parameters in 42 MS patients and 30 HCs. T1-weighted images were acquired and processed using CAT12 to perform vertexwise between-group comparisons of cortical thickness, gyrification, cortical complexity and sulcus depth with validated quality control protocols. We also performed SBM to analyze data from 19 patients with sleep disorders and 23 patients without sleep disorders. Compared with HCs, MS patients had differences in large clusters of cortical regions, especially in postcentral, precentral, superior frontal and paracentral thickness. Differences were also observed in the parietal and occipital areas. Among MS patients with and without sleep disorders, altered cortical complexity and sulcal depth were observed. This study strongly suggested that MS patients have cortical structural abnormalities compared with HCs, thus elucidating the underlying pathophysiology of motor and nonmotor symptoms in MS patients.

Retrospective analysis of spatiotemporal variation of scrub typhus in Yunnan Province, 2006-2022.

Scrub typhus is a life-threatening zoonotic infection. In recent years, the endemic areas of scrub typhus have been continuously expanding, and the incidence rate has been increasing. However, it remains a globally neglected disease. Yunnan Province is a major infected area, and the study of spatiotemporal and seasonal variation scrub typhus in this region is crucial for the prevention and control of the disease. We collected surveillance data on scrub typhus cases in Yunnan Province from 2006 to 2022. Using methods such as spatial trend analysis, Moran's I, and retrospective temporal scan statistics, the spatial and seasonal changes of scrub typhus were analyzed. The study period recorded 71,068 reported cases of scrub typhus in Yunnan Province, with the annual incidence rate sharply increasing (P<0.001). Approximately 93.38% of cases are concentrated in June to November (P = 0.001). Nearly 98.0% of counties were affected. The center of gravity of incidence migrates in a south and west direction. The incidence of scrub typhus was positively correlated spatially, and the spatial clustering distribution was significant. The most likely spatial cluster of cases (relative risk = 14.09, P<0.001) was distributed in Lincang, Dehong, Baoshan, Banna, and Puer. Significant positive correlations between the number of scrub typhus cases and average temperature, precipitation and relative humidity. In Yunnan Province, scrub typhus is widely transmitted, with an increasing incidence, and it exhibits distinct seasonal characteristics (from June to November). The center of gravity of incidence has shifted to the south and west, with higher incidence rates observed in border regions. The risk clustering regions encompass all border prefectures. This pattern is significantly correlated with climatic factors such as average temperature, precipitation, and relative humidity. The relevant departments should strengthen the monitoring of scrub typhus, formulate prevention and control strategies, and provide health education to local residents.

Research on Climate Drivers of Ecosystem Services’ Value Loss Offset in the Qinghai–Tibet Plateau Based on Explainable Deep Learning

As one of the highest and most ecologically vulnerable regions in the world, the Qinghai–Tibet Plateau (QTP) presents significant challenges for the application of existing ecosystem service value (ESV) assessment models due to its extreme climate changes and unique plateau environment. Current models often fail to adequately account for the complex climate variability and topographical features of the QTP, making accurate assessments of ESV loss deviations difficult. To address these challenges, this study focuses on the QTP and employs a modified ESV loss deviation model, integrated with explainable deep learning techniques (LSTM-SHAP), to quantify and analyze ESV loss deviations and their climate drivers from 1990 to 2030. The results show that (1) between 1990 and 2020, the offset index in the eastern QTP consistently remained low, indicating significant deviations. Since 2010, low-value clusters in the western region have significantly increased, reflecting a widening range of ecological damage caused by ESV losses, with no marked improvement from 2020 to 2030. (2) SHAP value analysis identified key climate drivers, including temperature seasonality, diurnal temperature variation, and precipitation patterns, which exhibit nonlinear impacts and threshold effects on ESV loss deviation. (3) In the analysis of nonlinear relationships among key climate drivers, the interaction between diurnal temperature range and precipitation in wet seasons demonstrated significant effects, indicating that the synergistic action of temperature variation and precipitation patterns is critical to ecosystem stability. Furthermore, the complex nonlinear interactions between climate factors exacerbated the volatility of ESV loss deviations, particularly under extreme climate conditions. The 2030 forecast highlights that wet season precipitation and annual rainfall will become key factors driving changes in ESV loss deviation. By combining explainable deep learning methods, this study advances the understanding of the relationship between climate drivers and ecosystem service losses, providing scientific insights for ecosystem protection and sustainable management in the Qinghai–Tibet Plateau.

Improvement of Sustainable Economic Mechanisms for the Formation of Tourist and Recreational Clusters in the Khorezm Region of the Republic of Uzbekistan

Objective: The study aims to create scientific and practical recommendations and proposals for enhancing the mechanisms of forming tourist and recreational clusters through innovative approaches, specifically tailored for application in the Republic of Uzbekistan. Method: Research was conducted through case studies, literature reviews, and data collection, focusing on identifying key factors in cluster formation, analyzing competitive tourism clusters, and developing strategies for the Khorezm region. Results and Discussion: The research focuses on enhancing the formation of tourist and recreational clusters in the Khorezm region of Uzbekistan through innovative approaches. It proposes organizing tourist complexes at various development levels, leveraging ecotourism and cultural-pilgrimage clusters such as "Khiva Smart," and developing zones like the "Amu Darya Ecological Zone." The study highlights the importance of public-private partnerships and the tourism potential of the region, with forecast values for growth in tourist flows between 2024-2027. Research Implications: Theoretically, the research introduces an innovative cluster formation model that can serve as a framework for future studies on tourism development, especially in regions with underutilized recreational potential. The findings also highlight the importance of seasonality in cluster planning, ensuring optimal resource allocation and long-term sustainability.