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Objective Emerging evidence suggests that gut microbiome composition alterations affect neurodegeneration through neuroinflammation in the pathogenesis of Parkinson’s disease (PD). Here, we evaluate gut microbiota alterations and host cytokine responses in a population of Taiwanese patients with PD. Methods Fecal microbiota communities from 80 patients with PD and 77 age and gender-matched controls were assessed by sequencing the V3–V4 region of the 16S ribosomal RNA gene. Diet and comorbidities were controlled in the analyses. Plasma concentrations of IL-1β, IL-2, IL-4, IL-6, IL-13, IL-18, GM-CSF, IFNγ, and TNFα were measured by a multiplex immunoassay and relationships between microbiota, clinical characteristics, and cytokine levels were analyzed in the PD group. We further examined the cytokine changes associated with the altered gut microbiota seen in patients with PD in another independent cohort of 120 PD patients and 120 controls. Results Microbiota from patients with PD was altered relative to controls and dominated by Verrucomicrobia , Mucispirillum , Porphyromonas , Lactobacillus , and Parabacteroides . In contrast, Prevotella was more abundant in controls. The abundances of Bacteroides were more increased in patients with non-tremor PD subtype than patients with tremor subtype. Bacteroides abundance was correlated with motor symptom severity defined by UPDRS part III motor scores (rho = 0.637 [95% confidence interval 0.474 to 0.758], P  < 0.01). Altered microbiota was correlated with plasma concentrations of IFNγ and TNFα. There was a correlation between Bacteroides and plasma level of TNFα (rho = 0.638 [95% CI: 0.102–0.887], P  = 0.02); and a correlation between Verrucomicrobia abundance and plasma concentrations of IFNγ (rho = 0.545 [95% CI − 0.043–0.852], P  = 0.05). The elevated plasma cytokine responses were confirmed in an additional independent 120 patients with PD and 120 controls (TNFα: PD vs. control 8.51 ± 4.63 pg/ml vs. 4.82 ± 2.23 pg/ml, P  < 0.01; and IFNγ: PD vs. control: 38.45 ± 7.12 pg/ml vs. 32.79 ± 8.03 pg/ml, P  = 0.03). Conclusions This study reveals altered gut microbiota in PD and its correlation with clinical phenotypes and severity in our population. The altered plasma cytokine profiles associated with gut microbiome composition alterations suggest aberrant immune responses may contribute to inflammatory processes in PD.

Gastrointestinal (GI) dysfunction is a common and often underappreciated aspect of Parkinson’s disease (PD), with symptoms manifesting at multiple levels of the digestive tract, from swallowing difficulties to challenges with defecation. These non-motor symptoms can be more debilitating than the hallmark motor impairments of PD, profoundly affecting patients’ quality of life. The burden of GI issues in PD extends beyond discomfort, contributing to malnutrition, weight loss, and impaired medication absorption, which can exacerbate both motor and non-motor symptoms. Despite their clinical significance, GI symptoms are frequently overlooked or mismanaged in routine practice. Inappropriate treatments, including certain medications and dietary recommendations, may inadvertently worsen the disease course. Therefore, a comprehensive understanding of GI dysfunction in PD is critical for clinicians, especially neurologists, to optimize patient care. This review provides an updated overview of the common GI manifestations in PD, including drooling, dyspepsia and dysphagia, gastroparesis, constipation, H. pylori infection, and small intestinal bacterial overgrowth. We discuss current diagnostic approaches, non-pharmacological and pharmacological treatment strategies. Recognizing and appropriately managing GI dysfunction in PD is essential for optimizing symptom control and improving patients’ overall well-being. Plain Language Summary Many people with Parkinson’s disease (PD) experience digestive problems, but these issues are often overlooked. Symptoms can affect the entire digestive system, from difficulty swallowing to trouble with bowel movements. In some cases, these problems can be more challenging than the movement difficulties caused by PD. Poor digestion can lead to malnutrition, weight loss, and problems absorbing medication, which may worsen both motor and non-motor symptoms. Unfortunately, digestive issues in PD are sometimes mismanaged, and certain treatments or dietary changes might make things worse. It is important for doctors to understand and properly address these symptoms. This article provides an updated overview of common digestive problems in PD, including drooling, difficulty swallowing, slow stomach emptying, constipation, and infections in the gut. It also discusses how these issues can be diagnosed and treated using both medical and non-medical approaches. Proper management of digestive problems can help improve the quality of life for people with PD.

It is generally accepted that the perception of homeowners towards certain potential risks or amenities fades as distance from the risk or amenity increases. This study aims to illustrate the distance–decay pattern with an appropriate mathematical function. Distance–decay functions and parameters that yield the minimum residual sum of squares (RSS) for a given regression model are considered to be the optimal approximation for the pattern of decay. The effect of flood risk and mass rapid transit (MRT) accessibility on residential housing prices in Taipei, Taiwan, are used as examples to test the optimization process. The results indicate that the type of distance function affects both the significance and the magnitude of the regression coefficients. In the case of Taipei, concave functions provide better fits for both the flood risk and MRT accessibility. RSS reduction is up to 10% compared to the blank. Surprisingly, the impact range for the flood risk is found to be larger than that for MRT accessibility, which suggested that the impact range of perception for uncertain risks is larger than expected.

Eutrophication is an environmental pollution problem that occurs in natural water bodies. Regression analyses with interaction terms are carried out to identify the factors influencing the Shimen, Mingde, and Fongshan Reservoirs in Taiwan. The results indicate that the main factor influencing these reservoirs is total phosphorus. In the Shimen and Mingde Reservoirs, the influence of total phosphorus, when interacting with other factors, on water quality trophic state is more serious than that of total phosphorus per se. This implies that the actual influence of total phosphorus on the eutrophic condition could be underestimated. Furthermore, there was no deterministic causality between climate and water quality variables. In addition, time lagged effects, or the influence of their interaction with other variables, were considered separately in this study to further determine the actual relationships between water trophic state and influencing factors. The influencing patterns for three reservoirs are different, because the type, size, and background environment of each reservoir are different. This is as expected, since it is difficult to predict eutrophication in reservoirs with a universal index or equation. However, the multiple linear regression model used in this study could be a suitable quick-to-use, case-by-case model option for this problem.

Treatment cost and quality of domestic water are highly correlated with raw water quality in reservoirs. This study aims to identify the key factors that influence the trophic state levels and correlations among Carlson trophic state index (CTSI) levels, water quality parameters and weather factors in four major reservoirs in Taiwan from 2000 to 2017. Weather (e.g., air temperature, relative humidity, total precipitation, sunlight percentage and cloud cover) and water quality parameters (e.g., pH, chemical oxygen demand, suspended solids (SS), ammonia, total hardness, nitrate, nitrite and water temperature) were included in the principal component analysis and absolute principal component score models to evaluate the main governing factors of the trophic state levels (e.g., CTSI). SS were washed out by precipitation, thereby influencing the reservoir transparency tremendously and contributing over 50% to the CTSI level in eutrophicated reservoirs (e.g., the Shihmen and Chengchinghu Reservoirs). CTSI levels in the mesotrophic reservoir (e.g., Liyutan Reservoir) had strong correlation with chlorophyll-a and total phosphorus. Results show that rainfall/weather factors were the key driving factors that affected the CTSI levels in Taiwan eutrophicated reservoirs, indicating the need to consider basin management and the impacts of extreme precipitation in reservoir management and future policymaking.

Background. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation to modulate cortical activity for improving motor function. However, the information of tDCS stimulation on different brain regions for dual task walking and cortical modulation in Parkinson’s disease (PD) has not yet been compared. Objective. To investigate the effects of different tDCS targets on dual task gait performance and cortical activity in patients with PD. Methods. 36 participants were randomly assigned to primary motor cortex (M1) tDCS, dorsal lateral prefrontal cortex (DLPFC) tDCS, cerebellum tDCS, or sham tDCS group. Each group received 20 min of tDCS stimulation, except the sham group. Gait performance was measured by GaitRite system during dual task walking and single walking. Corticomotor activity of tibialis anterior (TA) was measured using transcranial magnetic stimulation (TMS). The functional mobility was assessed using the timed up and go (TUG) test. Results. All participants showed no significant differences in baseline data. Following the one session tDCS intervention, M1 (P=0.048), DLPFC (P<0.001) and cerebellum (P=0.001) tDCS groups demonstrated significant improvements in dual task gait speed compared with pre-test. The time x group interaction (F(3,32)=5.125, P =0.005) were detected in dual task walking speed. The post-hoc Tukey’s test showed that the differences in gait speed was between sham tDCS group and DLPFC tDCS group (p=0.03). Moreover, DLPFC tDCS as well increased silent period more than M1 tDCS (p = 0.006) and sham tDCS (p = 0.002). Conclusion. Our results indicate that DLPFC tDCS exerted most beneficial effects on dual task walking and cortical modulation in participants with PD. Clinical Trial Registration: This trial was registered at the Thai Clinical Trials Registry (http://www.thaiclinicaltrials.org/show/TCTR20200909005).

Objective Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disorder caused by NOTCH2NLC GGC repeat expansions, with heterogeneous clinical manifestations, including parkinsonism. Recent studies have identified NOTCH2NLC repeat expansions in patients with Parkinson's disease (PD) and atypical parkinsonism (aPM), suggesting a potential genetic contribution. However, it remains unclear whether such cases represent NIID‐related parkinsonism or typical PD. To address this, we screened NOTCH2NLC repeat expansions in a parkinsonian cohort and analyzed associated clinical and neuroimaging features. Methods We examined 1017 unrelated patients with PD, 115 with aPM, 11 with multiple system atrophy, six with progressive supranuclear palsy, three with dementia with Lewy bodies, and 321 healthy controls. NOTCH2NLC GGC repeat expansions were detected using repeat‐primed PCR and amplicon length analysis. Clinical data and neuroimaging findings were comprehensively reviewed. Results Pathological NOTCH2NLC repeat expansions were identified in four patients with aPM and none with PD or in controls, with significantly higher frequency in aPM than in PD. An additional affected family member was also identified. All five patients showed clinical or neuroimaging features suggestive of NIID, including white matter hyperintensities in the paravermis and/or corticomedullary junction, curvilinear hyperintensities on diffusion‐weighted imaging. Skin biopsies in two patients revealed eosinophilic, p62‐positive intranuclear inclusions in the sweat gland cells and fibroblasts. No patient responded well to levodopa. TRODAT scans revealed normal findings in three patients, symmetric dopaminergic deficits in one, and asymmetric deficits in another. Interpretation NOTCH2NLC repeat expansions appear to be more frequently associated with aPM with NIID‐like features than with typical PD.

Background: Mutations in leucine-rich repeat kinase 2 (LRRK2) comprise a common genetic risk factor for Parkinson’s disease (PD) and inflammatory bowel disease. We investigated the expression of LRRK2 in colonic biopsies obtained from a cohort of PD patients and healthy controls. Methods: A cohort of 51 PD patients and 40 age- and gender-matched controls who have colonic biopsied samples were recruited. Among these participants, 26 individuals (12 PD patients and 14 controls) had a series of colon biopsies. For the patients with PD, the first biopsies were taken before the PD diagnosis. The colonic expression of LRRK2 was assayed by immunohistochemical staining. Results: The fraction of LRRK2-positive cells among the total cell count in biopsied colonic tissues was significantly higher in PD patients than controls (0.81%±0.53% vs. 0.45%±0.39%; P=0.02). Colonic LRRK2 immunoreactivity was higher in those with LRRK2 genetic variants compared to those with wild type LRRK2 (2.44%±1.15% vs. 0.21±0.13%, P<0.01). Age had no effect on LRRK2 expression (P=0.96). LRRK2 expression correlated with disease severity in regards to motor symptoms measured by the UPDRS part III scores (r=6335, P<0.001) and cognitive dysfunction measured by the mini-mental status examination scores (r=-0.5774, P<0.001). PD patients in the prodromal phase had a steeper increase in colonic LRRK2 expression compared to controls during the serial colon biopsy assessment (P<0.01). Conclusions: Colonic LRRK2 expression was increased in PD patients compared to controls, and the expression level correlated with disease severity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), universally recognized as COVID-19, is currently is a global issue. Our study uses multivariate regression for determining the relationship between the ambient environment and COVID-19 cases in Lima. We also forecast the pattern trajectory of COVID-19 cases with variables using an Auto-Regressive Integrated Moving Average Model (ARIMA). There is a significant association between ambient temperature and PM10 and COVID-19 cases, while no significant correlation has been seen for PM2.5. All variables in the multivariate regression model have R2 = 0.788, which describes a significant exposure to COVID-19 cases in Lima. ARIMA (1,1,1), during observation time of PM2.5, PM10, and average temperature, is found to be suitable for forecasting COVID-19 cases in Lima. This result indicates that the expected high particle concentration and low ambient temperature in the coming season will further facilitate the transmission of the coronavirus if there is no other policy intervention. A suggested sustainable policy related to ambient environment and the lessons learned from different countries to prevent future outbreaks are also discussed in this study.

Unlike carbon footprint in fossil fuel usage, few studies have investigated carbon footprint in the upstream petroleum industry. Currently, there is no published offshore carbon footprint study, and the carbon footprint of unmanned offshore platforms in Indonesia remains unclear. This study aims to identify the potential carbon footprint of offshore platforms in the Madura Field during offshore production based on the data activity using the life cycle approach. The data inventory had been monitored for a one-year natural gas production cycle from four unmanned platforms and one processing platform in Madura Field. The results show that the unmanned offshore platforms generated an average of 98.77 kg CO2eq/GJ with a high deviation (± 3.34). The processing platform’s average carbon footprint is 1232 kg CO2eq/GJ, which indicates the wide carbon footprint range between production platforms. Carbon footprint in the offshore platform is essential for completing the cradle to grave footprint identification since it is one of the important environmental sustainable indicators used as environmental evaluation tools. Understanding the footprint level in the upstream petroleum industry is significant for studying climate change’s impact on offshore activity, potential carbon generation released to the environment, and the key step of establishing a carbon reduction plan for the petroleum industry. Therefore, climate sustainability evaluation in the upstream petroleum industry can be assessed continuously.