Predictors of transition to schizophrenia and other long-lasting non-affective psychoses in first-episode patients with acute and transient psychotic disorders: A validation study

Background and objectives Almost half of the individuals with a first-episode of psychosis who initially meet criteria for acute and transient psychotic disorder (ATPD) will have had a diagnostic revision during their follow-up, mostly toward schizophrenia. This study aimed to determine the proportion of diagnostic transitions to schizophrenia and other long-lasting non-affective psychoses in patients with first-episode ATPD, and to examine the validity of the existing predictors for diagnostic shift in this population. Methods We designed a prospective two-year follow-up study for subjects with first-episode ATPD. A multivariate logistic regression analysis was performed to identify independent variables associated with diagnostic transition to persistent non-affective psychoses. This prediction model was built by selecting variables on the basis of clinical knowledge. Results Sixty-eight patients with a first-episode ATPD completed the study and a diagnostic revision was necessary in 30 subjects at the end of follow-up, of whom 46.7% transited to long-lasting non-affective psychotic disorders. Poor premorbid adjustment and the presence of schizophreniform symptoms at onset of psychosis were the only variables independently significantly associated with diagnostic transition to persistent non-affective psychoses. Conclusion Our findings would enable early identification of those inidividuals with ATPD at most risk for developing long-lasting non-affective psychotic disorders, and who therefore should be targeted for intensive preventive interventions. (AU)

Treatment patterns and survival outcomes in patients with non-metastatic early-onset pancreatic cancer.

BACKGROUND: The incidence of patients with early-onset pancreatic cancer (EOPC; age ≤ 50 years at diagnosis) is on the rise, placing a heavy burden on individuals, families, and society. The role of combination therapy including surgery, radiotherapy, and chemotherapy in non-metastatic EOPC is not well-defined. AIM: To investigate the treatment patterns and survival outcomes in patients with non-metastatic EOPC. METHODS: A total of 277 patients with non-metastatic EOPC who were treated at our institution between 2017 and 2021 were investigated retrospectively. Overall survival (OS), disease-free survival, and progression-free survival were estimated using the Kaplan-Meier method. Univariate and multivariate analyses with the Cox proportional hazards model were used to identify prognostic factors. RESULTS: With a median follow-up time of 34.6 months, the 1-year, 2-year, and 3-year OS rates for the entire cohort were 84.3%, 51.5%, and 27.6%, respectively. The median OS of patients with localized disease who received surgery alone and adjuvant therapy (AT) were 21.2 months and 28.8 months, respectively (P = 0.007). The median OS of patients with locally advanced disease who received radiotherapy-based combination therapy (RCT), surgery after neoadjuvant therapy (NAT), and chemotherapy were 28.5 months, 25.6 months, and 14.0 months, respectively (P = 0.002). The median OS after regional recurrence were 16.0 months, 13.4 months, and 8.9 months in the RCT, chemotherapy, and supportive therapy groups, respectively (P = 0.035). Multivariate analysis demonstrated that carbohydrate antigen 19-9 level, pathological grade, T-stage, N-stage, and resection were independent prognostic factors for non-metastatic EOPC. CONCLUSION: AT improves postoperative survival in localized patients. Surgery after NAT and RCT are the preferred therapeutic options for patients with locally advanced EOPC.

Chemokine expression in sera of patients with microscopic polyangiitis and granulomatosis with polyangiitis.

We evaluated chemokine expression and its correlation with disease activity in patients with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) (MPA/GPA). Serum CCL2, CCL4, CCL19, CXCL1, CXCL2, and CX3CL1 level in 80 patients were analysed using multiple enzyme-linked immunosorbent assays. Correlations between variables were investigated using Pearson's correlation analysis, and receiver operator curve analysis was performed to identify optimal CX3CL1 values in determining active disease. Multivariate logistic regression analysis was done to evaluate predictors of active disease. CCL4 (r = 0.251, p = 0.025), CXCL1 (r = 0.270, p = 0.015), and CX3CL1 (r = 0.295, p = 0.008) significantly correlated with BVAS, while CX3CL1 was associated with five-factor score (r = - 0.290, p = 0.009). Correlations were revealed between CCL2 and CCL4 (r = 0.267, p = 0.017), CCL4 and CXCL1 (r = 0.368, p < 0.001), CCL4 and CXCL2 (r = 0.436, p < 0.001), and CXCL1 and CXCL2 (r = 0.518, p < 0.001). Multivariate analysis revealed serum CX3CL1 levels > 2408.92 pg/mL could predict active disease (odds ratio, 27.401, p < 0.001). Serum chemokine levels of CCL4, CXCL1, and CX3CL1 showed association with disease activity and especially, CX3CL1 > 2408.92 pg/mL showed potential in predicting active MPA/GPA.

Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques.

The advent of Surface-Enhanced Raman Scattering (SERS) has enabled the exploration and detection of small molecules, particularly in biological fluids such as serum, blood plasma, urine, saliva, and tears. SERS has been proposed as a simple diagnostic technique for various diseases, including cancer. Renal cell carcinoma (RCC) ranks as the sixth most commonly diagnosed cancer in men and is often asymptomatic, with detection occurring incidentally. The onset of symptoms typically aligns with advanced disease, aggressive histology, and unfavorable prognosis, and therefore new methods for an early diagnosis are needed. In this study, we investigated the utility of label-free SERS in urine, coupled with two multivariate analysis approaches: Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM), to discriminate between 50 RCC patients and 44 healthy donors. Employing LDA-PCA, we achieved a discrimination accuracy of 100% using 13 principal components, and an 88% accuracy in discriminating between different RCC stages. The SVM approach yielded a training accuracy of 100%, a validation accuracy of 99% for discriminating between RCC and controls, and an 80% accuracy for discriminating between stages. The comparative analysis of raw and normalized SERS spectral data shows that while raw data disclose relative concentration variations in urine metabolites between the two classes, the normalization of spectral data significantly improves the accuracy of discrimination. Moreover, the selection of principal components with markedly distinct scores between the two classes serves to alleviate overfitting risks and reduces the number of components employed for discrimination. We obtained the accuracy of the discrimination between the RCC patients cases and healthy donors of 90% for three PCs and a linear discrimination function, and a 88% accuracy of discrimination between stages using six PCs, mitigating practically the risk of overfitting and increasing the robustness of our analysis. Our findings underscore the potential of label-free SERS of urine in conjunction with chemometrics for non-invasive and early RCC detection.

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis.

The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a hyperspectral imaging system, covering 472 wavebands from 400 to 1000 nm. Regions of interest (ROIs) were defined to extract average spectra from the hyperspectral images (HIS). We developed two models: least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) to establish a quantitative analysis between the pigment amounts and spectra. The spectra and pigment contents were predicted and correlated using these models. The selection of EWs for modeling was done using the Successive Projections Algorithm (SPA), regression coefficients (RC) from PLSR models, and LS-SVM. The results demonstrated that hyperspectral imaging could effectively evaluate the internal attributes of carrot cortex and xylem. Moreover, these models accurately predicted the Car and pH contents of the carrot parts. This study provides a valuable approach for variable selection and modeling in hyperspectral imaging studies of carrots.

Study of association between corneal shape parameters and axial length elongation during orthokeratology using image-pro plus software.

BACKGROUND: The aim was to validate the correlation between corneal shape parameters and axial length growth (ALG) during orthokeratology using Image-Pro Plus (IPP) 6.0 software. METHODS: This retrospective study used medical records of myopic children aged 8-13 years (n = 104) undergoing orthokeratology. Their corneal topography and axial length were measured at baseline and subsequent follow-ups after lens wear. Corneal shape parameters, including the treatment zone (TZ) area, TZ diameter, TZ fractal dimension, TZ radius ratio, eccentric distance, pupil area, and pupillary peripheral steepened zone(PSZ) area, were measured using IPP software. The impact of corneal shape parameters at 3 months post-orthokeratology visit on 1.5-year ALG was evaluated using multivariate linear regression analysis. RESULTS: ALG exhibited significant associations with age, TZ area, TZ diameter, TZ fractal dimension, and eccentric distance on univariate linear regression analysis. Multivariate regression analysis identified age, TZ area, and eccentric distance as significantly correlated with ALG (all P < 0.01), with eccentric distance showing the strongest correlation (ß = -0.370). The regressive equation was y = 1.870 - 0.235a + 0.276b - 0.370c, where y represents ALG, a represents age, b represents TZ area, and c represents eccentric distance; R2 = 0.27). No significant relationships were observed between the TZ radius ratio, pupillary PSZ area, and ALG. CONCLUSIONS: IPP software proves effective in capturing precise corneal shape parameters after orthokeratology. Eccentric distance, rather than age or the TZ area, significantly influences ALG retardation.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG.

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

Noninvasive Assessment of Chicken Egg Fertility during Incubation Using HSSE-GC-MS VOC Profiling.

Volatile organic compounds (VOCs) carry crucial information about chicken egg fertility. Assessing the fertility before incubation holds immense potential for poultry industry efficiency. Our study used headspace sorptive extraction-gas chromatography-mass spectrometry to analyze egg VOCs before and during the initial 12 incubation days. A total of 162 VOCs were identified. Hexanal was significantly higher in unfertilized eggs, whereas compounds such as propan-2-ol, propan-2-one, and carboxylic acids were higher in fertilized eggs. Furthermore, the obtained multiple logistic regression model outperformed the partial least-squares-discriminant analysis (PLS-DA) model, demonstrating lower complexity and superior performance. Fertile eggs were accurately identified in the validation set in 68-75% of the cases during the initial 4 days, to 85 and 100% on days 6 and 8. Finally, hierarchical cluster analysis in fertilized eggs revealed the clustering of VOCs of the same chemical class, indicative of their shared biochemical origin. This suggests a promising direction for future research aimed at understanding the biological information embedded in VOCs and their relationship to biochemical processes during embryo development.

Predicting survival in locally advanced gastric cancer using prognostic factors - neoadjuvant rectal score and downstaging depth score.

BACKGROUND: Clinical prediction models are needed to accurately predict the prognosis of patients with gastric cancer who have received neoadjuvant therapy and to determine the best treatment strategies. The aim of this study is to determine the role of two prognostic factors, the neoadjuvant rectal (NAR) score and the downstaging depth score (DDS), in predicting survival in patients with gastric cancer who received neoadjuvant therapy and underwent curative gastrectomy. METHODS: We reviewed the medical records of 129 patients who had been diagnosed with primary gastric cancer and underwent radical gastrectomy after receiving neoadjuvant therapy. We calculated the NAR score and DDS values for each patient and conducted a survival analysis to assess the accuracy of these prognostic factors in predicting overall survival. RESULTS: The median overall survival time of the patients was found to be 29 months. Patients with low NAR scores and high DDS had significantly longer overall survival. Univariate analyses based on clinical and laboratory characteristics showed that gender, surgery type, resection type, neural invasion, grade, adjuvant radiotherapy, lymphocyte level, carcinoembryonic antigen (CEA) level, NAR score, and DDS were associated with survival. Moreover, multivariate analyses showed that lymphocyte level, DDS, and NAR score were independent prognostic factors. CONCLUSION: In summary, our research indicates that NAR score and DDS may serve as useful prognostic markers for predicting overall survival in patients with locally advanced gastric cancer who receive neoadjuvant chemotherapy followed by curative surgery. Patients with high DDS and low NAR scores were found to have better prognoses.

Personalized analysis of pain-weather associations: a pilot study.

Background and purpose:

It is a wellknown belief that weather can influence human health, including pain sensation. However, the current data are controversial, which might be due to the wide range of interindividual differences. The present study aimed to characterize the individual pain–weather associations during chronic pain by utilizing several data analytical methods.

The study included 3-3 patients with (P1, P3, and P4) or without (P2, P5, P6) diabetes mellitus and signs of trigeminal neuralgia or low back pain. Subjective pain scores (0–10) and 12 weather parameters (terrestrial, geomagnetic, and solar) were recorded for one month repeated three times daily. Nonparametric Spearman’s correlation (Sp), multiple regression (Mx), and principal component (PCA) analyses were performed to evaluate associations between pain and meteorological factors obtained at the day of recorded pain value, 2 days before and 2 days after the recorded pain, and the changes in these parameters (5 × 12 parameters). Complex scores were calculated based on the results of these analyses.

While the temperature had the highest effects on the pain levels in most of the participants, huge interindividual dif­ferences in the degree and the direction of the associations between pain and weather parameters could be obtained. The analytic methods also revealed subjectspecific results, and the synthesis of different statistical methods as total scores provided a personalized map for each patient, which showed disparate patterns across the study participants. Thus, Participants 2 and 5 had higher scores for Mx compared to Sp; furthermore, certain factors showed opposite direction in their associations with the pain level depending on the type of analysis (Sp vs Mx). In contrast, P3 had a lower score for Mx compared to Sp, which might suggest a low level of weather sensitivity on the association between the different weather parameters in this subject. Furthermore, participants P4 and P6 had a very high level of weather sensitivity, while P1 had an opposite pattern. Regarding the time point-related effects on the pain level, most patients were sensitive to parameters obtained at the same day or two days before, except the P1 subject, who had the highest sensitivity to weather parameters detected two days after.

The present study highlights the importance of integrating different data analysis approaches to elucidate the individual connections between pain and most of the weather parameters. In conclusion, complex personalized profiling should be considered for the characterization of pain–weather associations by applying different data analytical approaches, which may provide feedback to physicians and patients. 

A mobile app to challenge obsessional beliefs in adolescents: a protocol of a two-armed, parallel randomized controlled trial.

BACKGROUND: Adolescence is a crucial stage for the development of OCD symptoms that, in most cases, persist into adulthood. This requires designing preventive strategies tailored to this population. Therefore, we aim to describe the study protocol that will be used to examine the effectiveness of a mobile health application to challenge obsessional beliefs in adolescents. METHODS: A two-armed randomized controlled trial will be conducted on an adolescent sample from the general population. The experimental group will use the intervention module (GGOC-AD) of a mobile app on the GGtude platform for 14 days whereas the control group will use a non-active module (GGN-AD) of said app. Primary outcome measures will be obsessional beliefs and obsessive-compulsive symptoms, and secondary measures will be self-esteem and emotional symptoms. Three assessment points will be conducted at baseline, post-intervention, and one-month follow-up. A linear multiple regression model with an intention to treat approach will be used. The expected total sample size will be 55 participants. DISCUSSION: We expect that the intervention group will show a reduction in obsessional beliefs and OCD-symptoms at post and follow-up in comparison with the control group. Additionally, we expect that the app will improve participants' self-esteem. This study could provide an accessible mobile health tool to prevent OCD-related symptoms in adolescents. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06033391 . Registered September 4, 2023.

Peripapillary atrophy area predicts the decrease of macular choroidal thickness in young adults during myopia progression.

OBJECTIVE: This study aimed to investigate the influence of peripapillary atrophy (PPA) area and axial elongation on the longitudinal changes in macular choroidal thickness (ChT) in young individuals with myopia. METHODS AND ANALYSIS: In this longitudinal investigation, 431 eyes-342 categorised as non-high myopia (non-HM) and 89 as HM-were examined for 2 years. Participants were examined with swept-source optical coherence tomography. The macular ChT, PPA area and axial length (AL) were measured at baseline and follow-up visits. Multiple regression analysis was performed to identify factors associated with ChT changes. The areas under the receiver operating characteristic curves were analysed to ascertain the predictive capacity of the PPA area and axial elongation for the reduction in macular ChT. RESULTS: Initial measurements revealed that the average macular ChT was 240.35±56.15 µm in the non-HM group and 198.43±50.27 µm in the HM group (p<0.001). It was observed that the HM group experienced a significantly greater reduction in average macular ChT (-7.35±11.70 µm) than the non-HM group (-1.85±16.95 µm, p=0.004). Multivariate regression analysis showed that a greater reduction of ChT was associated with baseline PPA area (ß=-26.646, p<0.001) and the change in AL (ß=-35.230, p<0.001). The combination of the baseline PPA area with the change in AL was found to be effective in predicting the decrease in macular ChT, with an area under the curve of 0.741 (95% CI 0.694 to 0.787). CONCLUSION: Over 2 years, eyes with HM exhibit a more significant decrease in ChT than those without HM. Combining the baseline PPA area with the change in AL could be used to predict the decrease of macular ChT.

Sociodemographic and clinical characteristics of people with ostomy and the adaptive domains of Roy's theory: A cross-sectional study.

INTRODUCTION: The adaptation of people with ostomies may be associated with and affected by sociodemographic and clinical factors. The present study aimed to investigate the association between the sociodemographic and clinical characteristics and the adaptation of people with an intestinal stoma. METHOD: An analytical study, carried out through an interview with 200 patients with ostomy for five months. For that, it was applied to scale for the level of adaptation of ostomy patients to measure the physiological domains, self-concept, role function and interdependence and a questionnaire was used in which sociodemographic and clinical information. Descriptive and multivariate analyses were performed to test the study hypothesis. RESULTS: The study pointed out statistically significant associations with male sex, age group below 60, low education level, Stoma time less than one year, below one minimum wage, temporary permanence criteria and presence of complications relation to low scores of adaptation. CONCLUSIONS: The association of sociodemographic and clinical factors with the measured adaptive modes provides important information for the planning of nursing care and other care providers, since it directs actions to the aspects that give greater adaptive difficulty to people with stomas and which are the focus of care nursing to this clientele.

Beyond visual integration: sensitivity of the temporal-parietal junction for objects, places, and faces.

One important role of the TPJ is the contribution to perception of the global gist in hierarchically organized stimuli where individual elements create a global visual percept. However, the link between clinical findings in simultanagnosia and neuroimaging in healthy subjects is missing for real-world global stimuli, like visual scenes. It is well-known that hierarchical, global stimuli activate TPJ regions and that simultanagnosia patients show deficits during the recognition of hierarchical stimuli and real-world visual scenes. However, the role of the TPJ in real-world scene processing is entirely unexplored. In the present study, we first localized TPJ regions significantly responding to the global gist of hierarchical stimuli and then investigated the responses to visual scenes, as well as single objects and faces as control stimuli. All three stimulus classes evoked significantly positive univariate responses in the previously localized TPJ regions. In a multivariate analysis, we were able to demonstrate that voxel patterns of the TPJ were classified significantly above chance level for all three stimulus classes. These results demonstrate a significant involvement of the TPJ in processing of complex visual stimuli that is not restricted to visual scenes and that the TPJ is sensitive to different classes of visual stimuli with a specific signature of neuronal activations.

Long-term skeletodental changes with early and late treatment using modified C-palatal plates in hyperdivergent Class II adolescents.

OBJECTIVES: To compare skeletodental changes between early and late treatment groups using modified C-palatal plates (MCPP) and long-term retention outcomes in hyperdivergent Class II adolescents. MATERIALS AND METHODS: Seventy-one hyperdivergent Class II patients were divided into four groups according to treatment modality and treatment timing: group 1, early treatment with MCPP (n = 16; 9.9 ± 0.9 years); group 2, late treatment with MCPP (n = 19; 12.3 ± 0.8 years); group 3, early treatment with headgear (HG; n = 18; 9.6 ± 0.8 years); and group 4, late treatment with HG (n = 18; 12.1 ± 1.2 years). Lateral cephalograms were taken and skeletal and dental variables were measured. For statistical analysis, paired t-tests, independent t-tests, and multiple regression were performed. RESULTS: The early MCPP group showed a more significant decrease in mandibular plane angle than the late MCPP group did, and vertical control was more efficient in the early group than in the late group. In the MCPP groups, both FMA and SN-GoGn were increased with late treatment but decreased with early treatment, and the difference was statistically significant (P < .01). The early-treatment MCPP group had a significant decrease in SN-GoGn of 0.6° compared with an increase of 1.7° in the early treatment HG group (P < .01). Posttreatment stability of both the early and late MCPP groups was maintained in long-term retention. CONCLUSIONS: Early MCPP showed more significant vertical control than late MCPP. However, there was no difference in long-term stability between early and late groups.

Preoperative anaemia in distal pancreatectomy: a propensity-score matched analysis.

BACKGROUND: Preoperative anaemia is a prevalent morbidity predictor that adversely affects short- and long-term outcomes of patients undergoing surgery. This analysis aimed to investigate preoperative anaemia and its detrimental effects on patients after distal pancreatectomy. MATERIAL AND METHODS: The present study was a propensity-score match analysis of 286 consecutive patients undergoing distal pancreatectomy. Patients were screened for preoperative anaemia and classified according to WHO recommendations. The primary outcome measure was overall morbidity. The secondary endpoints were in-hospital mortality and rehospitalization. RESULTS: The preoperative anaemia rate before matching was 34.3% (98 patients), and after matching a total of 127 patients (non-anaemic 42 vs. anaemic 85) were included. Anaemic patients had significantly more postoperative major complications (54.1% vs. 23.8%; p < 0.01), a higher comprehensive complication index (26.2 vs. 4.3; p < 0.01), and higher in-hospital mortality rate (14.1% vs. 2.4%; p = 0.04). Multivariate regression analysis confirmed these findings and identified preoperative anaemia as a strong independent risk factor for postoperative major morbidity (OR 4.047; 95% CI: 1.587-10.320; p < 0.01). CONCLUSION: The current propensity-score matched analysis strongly considered preoperative anaemia as a risk factor for major complications following distal pancreatectomy. Therefore, an intense preoperative anaemia workup should be increasingly prioritised.

Prediction of immunotherapy response in idiopathic membranous nephropathy using deep learning-pathological and clinical factors.

Background: Owing to individual heterogeneity, patients with idiopathic membranous nephropathy (IMN) exhibit varying sensitivities to immunotherapy. This study aimed to establish and validate a model incorporating pathological and clinical features using deep learning training to evaluate the response of patients with IMN to immunosuppressive therapy. Methods: The 291 patients were randomly categorized into training (n = 219) and validation (n = 72) cohorts. Patch-level convolutional neural network training in a weakly supervised manner was utilized to analyze whole-slide histopathological features. We developed a machine-learning model to assess the predictive value of pathological signatures compared to clinical factors. The performance levels of the models were evaluated using the area under the receiver operating characteristic curve (AUC) on the training and validation tests, and the prediction accuracies of the models for immunotherapy response were compared. Results: Multivariate analysis indicated that diabetes and smoking were independent risk factors affecting the response to immunotherapy in IMN patients. The model integrating pathologic features had a favorable predictive value for determining the response to immunotherapy in IMN patients, with AUCs of 0.85 and 0.77 when employed in the training and test cohorts, respectively. However, when incorporating clinical features into the model, the predictive efficacy diminishes, as evidenced by lower AUC values of 0.75 and 0.62 on the training and testing cohorts, respectively. Conclusions: The model incorporating pathological signatures demonstrated a superior predictive ability for determining the response to immunosuppressive therapy in IMN patients compared to the integration of clinical factors.

A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces.

Introduction: We use Spanish data from August 2020 to March 2021 as a natural experiment to analyze how a standardized measure of COVID-19 growth correlates with asymmetric meteorological and mobility situations in 48 Spanish provinces. The period of time is selected prior to vaccination so that the level of susceptibility was high, and during geographically asymmetric implementation of non-pharmacological interventions. Methods: We develop reliable aggregated mobility data from different public sources and also compute the average meteorological time series of temperature, dew point, and UV radiance in each Spanish province from satellite data. We perform a dimensionality reduction of the data using principal component analysis and investigate univariate and multivariate correlations of mobility and meteorological data with COVID-19 growth. Results: We find significant, but generally weak, univariate correlations for weekday aggregated mobility in some, but not all, provinces. On the other hand, principal component analysis shows that the different mobility time series can be properly reduced to three time series. A multivariate time-lagged canonical correlation analysis of the COVID-19 growth rate with these three time series reveals a highly significant correlation, with a median R-squared of 0.65. The univariate correlation between meteorological data and COVID-19 growth is generally not significant, but adding its two main principal components to the mobility multivariate analysis increases correlations significantly, reaching correlation coefficients between 0.6 and 0.98 in all provinces with a median R-squared of 0.85. This result is robust to different approaches in the reduction of dimensionality of the data series. Discussion: Our results suggest an important effect of mobility on COVID-19 cases growth rate. This effect is generally not observed for meteorological variables, although in some Spanish provinces it can become relevant. The correlation between mobility and growth rate is maximal at a time delay of 2-3 weeks, which agrees well with the expected 5?10 day delays between infection, development of symptoms, and the detection/report of the case.

The effect of spread through air spaces on postoperative recurrence-free survival in patients with multiple primary lung cancers.

PURPOSE: The purpose of the study was to investigate the effect of spread through air spaces (STAS) on the postoperative prognosis of patients with multiple primary lung cancers staged from IA to IB based on tumor size. METHODS: Clinicopathological and follow-up data of 122 patients with multiple primary lung cancers diagnosed at stages IA-IB and surgically treated at the Department of Thoracic Surgery, Shenzhen people's Hospital from January 2019 to December 2021 were retrospectively analyzed. The study involved 42 males and 80 females. STAS status was used to divide them into two groups (87 cases in STAS (-) and 35 cases in STAS (+)). A logistic regression analysis, univariate and multivariate Cox regression analysis, and Kaplan-Meier curves (K-M) were used to determine how STAS affected recurrence-free survival (RFS) in patients. RESULTS: STAS (+) had a significantly higher recurrence rate than STAS (-). STAS was predicted by smoking history (P = 0.044), main tumor diameter (P = 0.02), and solid nodules on chest CT (P = 0.02). STAS incidence was not significantly different between lobectomy and sublobar resection groups (P = 0.17). Solid nodules on CT, tumor diameter, vascular invasion, pleural invasion, and STAS were significant predictors of recurrence in the univariate Cox regression analysis. Tumor diameter, pleural invasion and STAS were significant prognostic factors for recurrence in the multivariate Cox regression analysis. Furthermore, STAS (+) group was at greater risk of recurrence than STAS (-) group (34% vs. 0%, P < 0.05)。. CONCLUSION: Stage IA-IB multiple primary lung cancer patients with STAS (+) had a higher recurrence rate and a shorter overall survival rate.

Exploring the Effect of Milk Fat on Fermented Milk Flavor Based on Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) and Multivariate Statistical Analysis.

Milk fat is a premium nutritional health product, yet there is a lack of high-fat dairy products for daily consumption in the current market. This study investigated the influence of different milk fat contents on the physicochemical and textural properties of fermented milk. The research revealed that an increase in milkfat content significantly improved the water-holding capacity, syneresis, color, hardness, springiness, gumminess, and chewiness of fermented milk, while showing minimal changes in pH and total titratable acidity. Response surface analysis indicated that fermented milk with 25% milk fat, 2.5% inoculum, a fermentation time of 16 h, and a fermentation temperature of 30 °C exhibited the highest overall acceptability. Using GC-IMS technology, 36 volatile compounds were identified, with an increase in milk fat content leading to elevated levels of ketone compounds, and 14 compounds were defined as key aroma compounds (ROAV > 1). Electronic nose distinguished samples with different milk fat contents. The results demonstrate that an increase in milk fat content enhances the physicochemical and flavor attributes of fermented milk. This work provides theoretical references for the production and development of high-fat fermented milk.